Patent Application
20240303171
This can relate to systems, methods, and computer-readable media for generating vulnerability reports supplemented with contextual data based on telemetry events obtained during operation of an application.
Security vulnerabilities in software packages are discovered by a number of different actors. For example, a software developer may discover a vulnerability during code development or code review, a quality assurance team might discover the vulnerability during testing, or a penetration tester may discover the vulnerability while conducting a security scan. As another example, which is exemplary of a worst-case scenario, an attacker could discover the vulnerability during an exploit scan.
If a user of a software package learns of the vulnerability in question, the user may want to know whether the software package is vulnerable. Some software packages are very large, and it may be unclear from the vulnerability disclosure information as to under which configuration or usage patterns the vulnerability exists. Furthermore, it is often the case that the vulnerability disclosure information is intentionally left vague to protect the intellectual property of the company or individual owning the vulnerable code.
Accordingly, what is needed is a more efficient and practical way to prioritize identified vulnerabilities with a software package.
Systems, methods, and computer-readable media for prioritizing vulnerability reports with telemetry events obtained during operation of an application.
This Summary is provided to summarize some example embodiments, so as to provide a basic understanding of some aspects of the subject matter described in this document. Accordingly, it will be appreciated that the features described in this Summary are merely examples and should not be construed to narrow the scope or spirit of the subject matter described herein in any way. Unless otherwise stated, features described in the context of one example may be combined or used with features described in the context of one or more other examples. Other features, aspects, and advantages of the subject matter described herein will become apparent from the following Detailed Description, Figures, and Claims.
The above and other aspects of the disclosure, its nature, and various features will become more apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings, in which like reference characters may refer to like parts throughout, and in which:
Systems, methods, and computer-readable media for evaluating a software application are provided and described with reference to
Systems, methods, and computer-readable media for prioritizing vulnerability reports with telemetry events and contextual data obtained during operation of an application are provided and described with reference to
Systems, methods, and computer-readable media for generating drift reports that show changes between different builds of an application are provided and described with reference to
As defined herein, an alert is an abnormal condition that has been identified by an analytics service, based on a rule defined in an alert grammar.
As defined herein, an alert grammar includes a set of rules or parameters that are used to classify telemetry events obtained by a telemetry interception and analysis platform (TIAP) during operation of an application. The set of rules can be part of default set of rules provided by the TIAP, generated by a customer using the TIAP, heuristically learned rules created by machine learning, or any combination thereof. Other grammars may be used by the TIAP such as, for example, insight grammars, performance grammars, and warning grammars. Yet other grammars can include compliance grammars that search telemetry data for specific items such as, for example, credit card numbers, personally identifiable information (PII), addresses, bank accounts, etc.
As defined herein, an analytics service refers to one of many services handled by the TIAP and operative to perform analytics and telemetry events collected from an application. The analytics service may reference an alert grammar, insight grammar, performance grammar, or any other grammar to evaluate collected telemetry events.
As defined herein, an application refers to a top hierarchy level of monitoring by the TIAP. An application includes one or more component groups and represents a complete implementation of a top-line business application.
As defined herein, an API Server is a service that implements endpoint APIs (REST-based) for use by user interface (UI) and command line interface (CLI) tools.
As defined herein, a blueprint service analyzes recorded telemetries for one or more components and creates alert rules based on what has been seen. The blueprint service can be used to define behavioral blueprints that describe the intended behavior of an application (e.g., how an application should be behave, what it should do, and what it should not do).
As defined herein, a component is abstract definition of a single type of process known to the platform (e.g., “database” or “web server”). An application can operate using one or more components.
As defined herein, a component instance is an individual concrete example of a component, running on a specific host or a virtual machine (e.g., “database running on myserver.corp.com”). One or more instances may occur for each component.
As defined herein, a component group is a collection of all instances of a given component (e.g., “all databases in application x”).
As defined herein, a common vulnerability and exposure (CVE) is a system that provides a reference-method for publicly known information-security vulnerabilities and exposures. The National Cybersecurity FFRDC, operated by the Mitre Corporation, maintains the system, with funding from the National Cyber Security Division of the United States Department of Homeland Security. The system was officially launched for the public in September 1999. The Security Content Automation Protocol uses CVE, and CVE IDs are listed on MITRE's system as well as in the US National Vulnerability Database.
As defined herein, a CVE service is a platform service that periodically ingests CVE metadata and analyzes if any components are vulnerable to any known CVEs.
As defined herein, a dashboard can refer to a main screen of a TIAP portal UI.
As defined herein, a drift report can show changes from one build of an application to another build of an application or to combination of other application builds.
As defined herein, a drift policy can specify which drift policy elements are monitored and compared to generate the drift report.
As defined herein, drift policy elements can include data obtained by a TIAP runtime or a TIAP portal. Examples of drift policy elements can include telemetry, alerts, standard build of materials, component remediation, component version, etc.
As defined herein, an event service is a service that responds to telemetry event submissions using a remote call (e.g., gRPC or representational state transfer (REST)) and stores those events in an events database.
As defined herein, a housekeeping service is a service that periodically removes old data from logs and databases.
As defined herein, an insight is a noncritical condition that has been identified by the analytics service, based on a rule defined in a grammar. Insights are typically suggestions on how performance or other software metrics can be improved, based on observed telemetries.
As defined herein, a native library refers to a collection of components or code modules that are accessed by the application.
As defined herein, an interception library is created by the TIAP and is used to intercept API calls by the application and record the API calls as a telemetry event. The interception library can trampoline the original API call to the native library. The interception library can include the same functions of the native library or subset thereof and any proprietary APIs, but is associated with analysis platform and enables extraction of telemetry events related to operation of the application. When a function is called in the interception library, the telemetry event collection is performed and actual code in the native library is accessed to implement the function call.
As defined herein, a TIAP portal may refer to a Software as a Service (SaaS) or on-premise management server that host TIAP, including the dashboard and other TIAP UI screens, as well as any services required to set up installation of TIAP runtime code to monitor a customer's application, collect telemetry from the customer's application, and analyze collected telemetry.
As defined herein, a metric can refer to telemetry data collected that includes a numeric value that can be tracked over time (to form a trend).
As defined herein, a policy may be a security ruleset delivered to the runtime during initial communication/startup that describes desired tasks that are to occur when certain events are detected (e.g., block/allow/warn).
As defined herein, TIAP runtime or Runtime refers to a code module that runs within a loaded process' (component instance) address space and provides TIAP services (e.g., telemetry gathering, block actions, etc.).
As defined herein, a trampoline or trampoline function is a runtime internal technique of hooking/intercepting API/library calls used by a component.
As defined herein, a trend is a change of metric values over time.
As defined herein, a vulnerability report associates a known vulnerability (e.g., a CVE) with a function, module, or object called by an application.
As defined herein, a warning is an abnormal condition that may not be critical, that has been detected by the analytics service, based on a rule defined in an alert/insight/warning grammar.
Software vulnerabilities may be present in any part of an application's source code. This can include code both written in-house by an organization and code that the organization imports from third party sources. Vulnerability information sources (CVE databases) can be used to learn if a particular code module has a vulnerability (and if so, how severe it is). Vulnerability prioritization can mean determining which CVEs need to be fixed in which order (high to low priority). One key input in this decision is understanding which dependencies are actually used by an application; simply having a vulnerable component packaged with the application but never used may mean that the affected CVEs can be deprioritized for remediation.
To ascertain whether or not a component is used, the TIAP needs to understand what “used” really means. For example, is a component used if it is loaded into memory? Is a component used if it is loaded into memory but not executed? To answer these questions, the TIAP can take into consideration the programming language and environment the application is written in and being run in. For a compiled language like C/C++, the TIAP can consider usage to mean “when the application loads a module into the process (shared library load, for example).” For JIT compiled languages like Java, the TIAP can consider usage to mean “when a class file containing compiled bytecode is loaded by the Java virtual machine.” For scripted languages, such as Python, PHP, and NodeJS (amongst others), the TIAP can consider usage to mean “when a language-specific file (.py, .js, .php, for example) is opened by the scripting language interpreter. Knowing which file(s) are opened by a scripting language interpreter can facilitate correlating CVEs with dependency packages (NPM modules, Ruby gems, Python modules, etc.). This correlation can then be used by embodiments discussed herein to provide usage based correlation and the ability to conclusively determine if a piece of software is susceptible to a vulnerability in a third party component.
The operating system 130 may include a UNIX-like operating system, such as the Linux operating system, iOS operating system, Mac OSX operating, or Windows operating system. Operating system 130 can include a kernel 131 and operating system modules 132. Operating system modules 132 can include components of operating system 130 other than kernel 131.
Other modules can include TIAP runtime module 110, telemetry module 112, instrumentation module 116, and applications module 120. Application module 120 may include computer-readable code for executing an application running on computer 100. The code may include executable code (e.g., a .exe file). Application module 120 may include a native library 125 (e.g., Libc.so) that is used during operation of the application. Native library 125 may include one or more components 126.
TIAP runtime module 110 may include computer readable code for executing operation of telemetry module 112 and instrumentation module 116, referred to herein as TIAP runtime or TIAP runtime code. TIAP runtime module 110 may include the TIAP runtime operative to collect telemetry events and provide the collected telemetry events to TIAP portal 160 via Internet 150.
Telemetry module 112 can include computer-readable code that is operative to intercept application programming interface (API) calls originating from the application at the library level within the software stack and capture such calls as telemetry events that are provided to TIAP 160 for further analysis. Telemetry module 112 may include an interception library 114. Interception library 114 may include interception code and trampoline functions corresponding to each component or API called by the application. The TIAP runtime can interpose on any function in any library used by any component by inserting interception hooks or trampoline functions into the application's dependency chain (e.g., IAT/PLT/GOT). These trampoline functions redirect control flow from the native library API functions to the TIAP runtime, which then collects information about the API request (parameters, call stack information, performance metrics, etc.) as telemetry events, and then passes the original call to the native library. The interception code is responsible for collecting the parameters needed for the telemetry event. Telemetry events can be continually monitored by the TIAP runtime. Each component instance is continually monitored by the TIAP runtime and the desired telemetry events are captured and sent to TIAP portal 160 Telemetry events can be collected into batches and periodically sent to the TIAP portal for later analysis. The batching capability of the platform runtime can be further subdivided into prioritized batches—this entails creating multiple event queues that are sent with varying priorities to TIAP portal 160. This subdivision is useful in scenarios where the runtime is only allotted a small amount of CPU/memory/network bandwidth (as to not interfere with efficient application execution). In the case where events may be dropped (due to not having sufficient resources), the TIAP runtime can instead collect a count of “missed events” that can be later communicated to the management platform when resources are available. This count provides the system administrator with a sense of how many events may be missing from the overall report provided by TIAP portal 160.
Instrumentation module 116 may be operative to load or package the necessary files and/or library associated with an application with files and/or library associate with platform 118 into a loader, launcher, or executable file that enables telemetry module 112 to extract telemetry events from the application during TIAP runtime.
Report module 182 may be operative to generate reports for display on a user interface. The reports can be vulnerability reports that include many useful categories of information for a component. The various information can be populated with telemetry data obtained by the TIAP runtime. For example, the information can include a version of a programming language, a version of a container image, a hypervisor type, a cloud service provider, and a container runtime. Other categories of information may also be displayed. Users can define what information is included in the report by interfacing with TIAP portal 160 and the user can save his or her preferences.
Drift module 192 may be operative to enforce a drift policy to compare one build to another build or to several prior builds. Drift module 192 can provide drift analysis that provides the ability to compare a set of builds and determine when and where a specific issue (e.g., security vulnerability) was introduced. Drift module 192 may enable a user to define a drift policy that defines what telemetry or alerts should be compared. Users can define the drift policy by interfacing with TIAP portal 160. The drift policy can be defined to compare file operation related alerts, software bill of materials (SBOM), network access, etc.
TIAP portal 160 may perform analytics on the collected telemetry events and generate visuals for display to users of computer 100 based on the analytics obtained from the analysis of the application.
Starting with block 202, an application can make an application programming interface (API) call (e.g., open, write, read, etc.). That call is passed to block 204 where a library (e.g., Libc.so) is accessed to execute the API call. The library can contain subroutines for performing system calls or other functions. At block 206, a system call is invoked. The system call may be a modification of an existing system call generally available from the operating system. For example, the system call may be a modified version of the ioctl system call. The system call may be invoked by filling up register values then asserting a software interrupt that allows trapping into kernel space. For example, block 206 may be performed by a C language program that runs in the Linux operating system. The C language program may move the system call's number into the register of a processor and then assert an interrupt. The invocation of the system call can be made using a programming language's library system call interface. In one embodiment, the invocation of the system call is made using the C programming language's library system call interface.
In block 208, the invocation of the system call executes a trap to enter the kernel space. The system call dispatcher gets the system call number to identify the system call that needs to be invoked.
In block 210, the system call dispatcher vectors branches to the system call, which in the example of
The TIAP according to embodiments discussed herein can intercept operations originating from the application at the library level of the software stack. This is in contrast with conventional hook operations that intercept at the system call level or somewhere within the kernel space, typically accessed using Extended Berkeley Packet Filter (cBPF). Hooks using eBPF are often subject to various issues such as software updates to parts of the software stack that require special permissions, administrator permissions, or lack of API assurance that can result in breaking the application. Therefore, to eliminate such issues, embodiments discussed herein intercept at the library level. Referring now to
The interception library can include the same functions of the native library or subset thereof and any proprietary APIs, but is associated with analysis platform and enables extraction of telemetry events related to operation of the application. When a function is called in the interception library, the telemetry event collection is performed and actual code in the native library is accessed to implement the function call. Telemetry events are shown in block 310. The interception library can enable all parameters of the API call to be recorded in a telemetry event. For example, if the API call is an OPEN command, the parameters can include file path, permissions, identification information, environmental information, etc. Since applications are continually monitored using embodiments discussed herein, telemetry events are constantly being collected and provided to the TIAP portal (e.g., portal 160). For example, the telemetry events may be queued at block 312 and batch transmitted to the analysis platform (block 316) each time a timer elapses at decision block 314. The TIAP portal can be run locally on the same device that is running the application or the analysis platform can be run remotely from the device running the application. In the remote case, the telemetry events may be transmitted via a network connection (e.g., the Internet) to the TIAP portal.
Telemetry events collected by the TIAP runtime can be buffered in memory into a lock-free queue. This requires little overhead during program execution as the telemetry upload occurs less frequently. The size of the event queue is determined by a setting periodically refreshed by the TIAP portal. The customer is permitted to set the amount of memory and CPU overhead that the TIAP runtime can consume. The TAP runtime can adjust the size of the event queue and the quality of data measured accordingly. In the case that events need to be dropped due to exceeding the allowed CPU/memory thresholds, a simple counter can be maintained to reflect the number of dropped events. When there is adequate resource available, the number of missed events is communicated to the TIAP platform. The buffer can be flushed periodically, depending on size and overhead constraints. This is done at event submission time (e.g., any event can potentially trigger a buffer flush). During flush, the events in the queue are batched and sent to an event service in the TIAP portal using REST or gRPC. The TIAP runtime can also support a high-priority queue, for urgent events/alerts.
The TIAP runtime may be required to handle special cases. The special cases can include handling signals, handling dynamic library loads, and handling fork and exec functions. Signal handling is now discussed. Telemetry events occurring during signal handling have to be queued in a way that uses no signal-unsafe APIs; this is the exception to the rule that that any event can cause a buffer flush. All trappable signals are caught by the runtime. The runtime increments counts of received signals for periodic upload to the management portal. In order to support the component's own use of signals, the runtime retains a list of any handlers the component registers using sigaction and invokes those handlers upon receiving a signal. This may require removing a stack frame before calling the handler.
The runtime intercepts call to the dlsym, dlopen, and other dynamic library load routines. These loaded libraries are subject to the same telemetry grammar treatment as during initial load. Calls to these functions also may result in telemetry events of their own.
The fork and exec functions require special treatment. Fork can result in an exact copy of the process being created, including a TIAP runtime state. In order to support fork properly, the fork call is intercepted and the following sequence of operations is performed: a fork telemetry event is sent (if such a telemetry grammar exists), the child's event queues are cleared, and the child's instance ID is regenerated. This sequence of steps ensures that the TIAP portal sees a clean set of telemetries from the child. The exec function requires other special treatment. On exec, the following sequence of operations is performed: the original arguments to exec are preserved, the arguments to exec are changed to point to the current program (e.g., the program that is already loaded), with no command line arguments and an environment variable named DF_EXEC set to the original arguments supplied by the caller. As a result, the operating system re-executes the same program, causing the runtime to restart itself. Upon seeing DF_EXEC set, the runtime will launch the original program defined in the call to exec, with runtime protection.
Immediately after the application call is sent to block 304, the original call command is invoked at block 306. Calling the original command is necessary to allow the application to operate as intended. The operations in blocks 304, 306, 310, 312, 314, and 316 may be executed by TIAP runtime module 110 or telemetry module 112. The original call command accesses the native library at block 307. This leads to a system call at block 308, and then access to the kernel at block 309.
It should be understood the flowchart can be implemented in any process being used by a customer application product. For example, the flowchart can be implemented in a web server, a database, middleware, or any other suitable platform being used by the application. That is, the same interception library can be used in all processes. This enables a history of the stack trace to be captured and analyzed.
Loader 440 can enable application 410 to load code in a library to be executed. For example, assuming that interception library is not present and the call CMD1411 is called. The loader would load the code 421 in native library so that the CMD1 operation could be executed. However, in the embodiment illustrated in
An alternative to using a preloader is to use an integrated loader (e.g., integrated loader 500) for each application. This integrated loader can eliminate a few potential issues that may exist with using the preloader. For example, a customer could turn the preloader off, which would prevent telemetry collection because the interception library would not be accessed first. Another potential issue that can arise using the preloader is that other resources may use it, thereby potentially causing who goes first management issues. In addition, if an application uses static linking (e.g., where code in the native library is copied over to the application), the pre-loader will not work.
The system loader is a program that is built on the TIAP and downloaded by a user to their workstation or build infrastructure machine. The system loader is typically part of a command line interface tool. In some embodiments, command line interface (CLI) tool 620 can be custom built for each customer as it will load components for that customer only. In other embodiments, CLI tool 620 is generic tool provided to each customer that enables the customer to build a different interception library for each application. The TIAP 630 can create the custom CLI tool (containing the system loading function) by using a link kit installed in the portal. The link kit includes a set of object files (.o files) that are linked against a customer-specific object file built on demand (from a dynamic code generation backend placing various statements into a .c file and compiling to an object file). This produces a customer specific CLI tool that contains all information required to produce a binary keyed to the customer that downloaded the CLI tool. This per-customer approach to CLI tool generation eliminates the need for the customer/user to enter many tenant-specific details when loading components. The CLI tool may also contain any SSL certificates or other items required for a secure transaction with the management portal. In other approaches, the SSL certificates can be obtained from an “API token,” which substitutes embedding the SSL certificate into CLI tool 620. The CLI tool can provide several functions: loading, showing/managing applications and components, showing telemetry events, showing audit logs, and showing alerts and metrics At a high level, the CLI tool offers a command line interface to much of the same functionality offered by the web UI provided by the TIAP portal.
During system loading, CLI 620 can receive build artifact 610 and generate interception library 640 by developing interception code for each component in the build artifact 610. The interception code can include telemetry grammars that define which events should be monitored for and recorded. The interception code can also include a trampoline function that transfers the application call to the native library so that the original call by the application is executed as intended. That is for each component of an application, application executable, or build artifact, a TIAP based interception code is generated and included in interception library 640. For example, if first command code is being processed, CLI 620 can send that first command to platform portal 630 via remote call 625. Portal 630 can assign that command a component ID 635 and pass it back down to CLI 620. This way when telemetry events are collected, the component ID will match with the component ID assigned by portal 630. CLI 620 can populate interception library 640 with each component of build artifact 610. When the interception library is complete, CLI 620 can provide the output to container 650, launcher 660, or integrated loader 670. Container 650 can be a class, a data structure, or an abstract data type whose instances are collections of other objects. Launcher 660 is akin to the preloader concept discussed above in connection with
Protection of non-executable artifacts is also possible. To protect interpreted scripts or languages, the system loader can provide a special launcher mode that produces a special binary containing only the TIAP runtime. When using launcher mode, the special binary executes a command of the customer's choice, as if the command being executed was already contained within the output. This allows for scenarios where interpreted languages are used and it is not determinable which interpreter may be present in the target (deployment) machine (as such interpreters may vary between the build environment and the deployment environment).
The CLI tool has various subcommands that are specified on the command line, such as ‘load’, ‘applications’, ‘components’, etc. The load subcommand can run in one of two modes: default and launcher. Each mode produces a different type of output file. In the default mode, which produces an integrated launcher of
A list of telemetry grammars is built into the loaded component. This occurs at application registration time (e.g., during system loading, when the component and application are being registered with the TIAP). The TIAP can provide a preconfigured set of interesting/well-known telemetry grammars that are automatically available as part of this transaction. Customers can override, customize, or remove any of these grammars using a user interface in a TIAP management portal (or the CLI tool). Customers can also define their own telemetry grammars, if they wish to collect additional telemetries not present in the TIAP common set.
The default set of telemetry grammars is stored in the TIAP's configuration database, and cloned/copied for each customer as they register with TIAP; this allows the customer to make any customizations to the default set they wish, if desired. Each set of customer-specific telemetry grammars are stored with the customer data in the configuration database (albeit separate from the default set or other customers' sets).
In launcher mode, the input is not specified using the −i argument, but rather with a −I (capital I). Launcher mode may be akin to the pre-loader of
If the system loader is being run in default mode and a non-executable file is specified as an input, the system loader will abort and recommend launcher mode instead. If the system loader registers a component that already exists in the TIAP, the system loader will abort and inform the user of this.
During component registration, a set of telemetry grammars will be sent to the system loader from the TIAP. These telemetry grammars contain a list of the libraries and APIs that should be intercepted for this component.
Both system loading modes accept a-t argument that contains a freeform string to be interpreted by the platform as the build time tag. This will typically be a comma separated set of key value pairs that the customer can use to assign any metadata to this component. Note that build time tags are included in the determination of any duplicate components.
The TIAP runtime is executable code that runs at process launch. It is built as position-independent code (PIC) and/or position-independent executable (PIE), and self-relocates to a random virtual address immediately upon startup. The runtime first performs a self-integrity check (to the extent possible considering the platform in use), and then performs a one-time survey/data collection of the following information: platform query, kernel version, memory, CPU (number, type, and speed), NUMA information, distribution information, and network/hardware information. The runtime then performs a transaction with the TIAP portal, sending the aforementioned data as part of a “component start” event. The TIAP portal may reply to this event by (1) proceed with start or (2) do not start. Additionally, the TIAP portal can inform the component that the host software catalogue is out of date by returning such a status code along with the component start event reply.
A host software catalogue is a list of software packages and constituent files on the machine running the component, indexed by hostname and IP address. This information is periodically gathered and uploaded to the TIAP portal to assist with analytics (specifically a common vulnerabilities and exposures (CVE) service). This catalogue is periodically updated, and the TIAP portal will report back out of date if the catalogue does not exist at all, or if the component loading date is later than the last catalogue update time, or if a set age threshold is exceeded (typically set to 1 week by default). If the TIAP portal requests a new catalogue to be uploaded, the runtime will compile the catalogue in a background thread and upload it to the portal when complete (asynchronously, low priority thread). The runtime either then starts the loaded or launched program, or, if the environment DF_EXEC is set, the value of that environment variable's content is used as the launched command line, overriding any −I (launch command) arguments.
On startup, the TIAP runtime can act as a replacement for the system run-time link-editor. The run-time link-editor (“loader”) resolves symbols from required libraries and creates the appropriate linkages. The TIAP runtime can redirect any function names specified in the trampoline grammar to itself, resulting in the creation of a trampoline. A trampoline function takes temporary control over program code flow performs the desired telemetry collection, calls the original function, and then queues an event to the event queue (if the grammar specifies that the API return value or function timing information is to be collected—otherwise the event is sent before the original function is called).
Static binaries pose a different challenge in the sense that there are typically no imports listed in the executable header. The runtime must perform a “hunt and patch” operation, in an attempt to find the corresponding system call stubs that match the function listed in the telemetry grammar. This can involve the following extra steps: searching through memory regions marked executable for system call (syscall) instructions, handling polymorphic syscall instructions (syscall opcodes buried within other instructions; false positives), handling just in time compiled (JITed) code, and handling self-modifying code. JITed and self-modifying code can be detected by mprotect(2) calls-code behaving in this way will be attempting to set the +X bit on such regions. Certain well known languages that output code using these approaches can be handled by out-of-band knowledge (such as hand inspection or clues/quirks databases).
After a customer's product has been configured to operate with the TIAP, telemetry events can be collected. These events can be communicated to the TIAP using an event API. Each “instrumented” component of the customer's application may be able to access the event API to communicate events. The communicated events may be processed by an event service running on the TIAP. The event service can be implemented as a gRPC endpoint running on a server responsible for the component. When the TIAP runtime detects an event of interest, a gRPC method invocation is invoked on the event service. The TIAP runtime knows the server (and consequently, event service) it will communicate with as this information is hardcoded into the runtime during initial loading of that component. Certain common events may occur often (e.g., opening the same file multiple times). In this case, the component may submit a “duplicate event” message which refers to a previous event instead of a completely new event message. This reduces traffic to the server.
The telemetry grammars runtime can define a telemetry level for each component or component instance. The telemetry levels can be set to one of many different levels (e.g., four different levels). Telemetry levels govern the quantity of events and data sent from the instance to the event service in the TIAP portal. Several different telemetry levels are now discussed. One telemetry level may be zero or none that enables the runtime to perform as a passthrough and sends only component start and exit events. Another level may be a minimal level in which the runtime sends only component start events, component exit events, metadata events, and minimal telemetry events. In this level, the runtime only communicates basic information such as the number of file or network operations/etc. Yet another level may be a standard level in which the runtime sends every type of event defined for the minimal level, plus events containing telemetry about the names of files being opened and lists of 5-tuple network connection information. In this level, file events will contain only a file name plus a count indicating the number of times that file was opened. Similarly, this level conveys the list of 5-tuples and a count of how many times that 5-tuple was seen. The standard level also sends event telemetry for the count of each 3rd party API used (count and type). Yet another level is the full level in which the runtime sends all events, including a separate event for each file and network access containing more information about the access, a separate event for each API access, etc. The full telemetry model may buffer events in the instance's filesystem locally before uploading many events in bulk (to conserve network bandwidth).
The telemetry levels can be configured in a variety of different ways. A default telemetry level can be set when the application or component is loaded. If desired any default telemetry level can be overridden at runtime by a runtime tag. The telemetry level can be set by an administrator using the TIAP portal. The administrator can override either of the above settings using a per-instance/component group/application/dashboard setting for the desired telemetry level. Telemetry levels are communicated back to the component multiplexed with the return status code for any event.
The telemetry events can be configured to adhere to a specific message structure. The message structure may be required to interface with the protocol buffers or Interface Definition Language (IDL) used by the event service. Each event can include two parts: an event envelope and an event body. The event envelope can include a header that contains information about the classification/type of the event, and information about the runtime that generated the event. The event body can include a structure containing the event information. This structure is uniquely formatted for each different type of event.
The event envelope can include several different fields. Seven fields are shown in the example pseudocode above. One field is the component_id field. This field includes the universally unique identifier (UUID) of the component making the event submission. This ID is created during loading and remains constant for the lifetime of the component. Note that there can be multiple component instances with the same component ID. Another field is the event_id field. This is the UUID of the event being submitted. This ID is selected randomly at event creation time. Event IDs can be reused by setting a ‘duplicate’ flag. Another field is the uint64 timestamp field which represents of the number of seconds since the start of a component instance (e.g., standard UNIX time_t format) when the event occurred. Yet another field is the timestamp_us-uint64_t which is a representation of the number of microseconds in the current second since the start of the component instance (e.g., standard UNIX time_t format) when the event occurred. Another field is the duplicate field which is set to true to indicate this event is a duplicate of a previously submitted event, and varies only in timestamp. A build_tag field contains the build time tag assigned to the component submitting the event, if any. A runtime_tag field contains the runtime (environment variable sourced) tag assigned to the component instance submitting the event, if any.
If the duplicate field is set to 1, this indicates that the event with the supplied event_id has occurred again. In this scenario, the event service will ignore any other submitted values in the rest of the message, except for the updated/new timestamp values.
Many different types of telemetry events can be collected. Each of these event types can be processed by the event service running on the TIAP. Several event types are now discussed. One event type is a component start event, which is sent when the component starts. This event includes information about the component, runtime, host platform and library versions, and other environmental data. Component start events are sent after the runtime has completed its consistency checks and surveyed the host machine for infrastructure-related information.
An IDL can describe two enumerations used in this event type: architecture_type and OS. Architecture type is enumerated by a value indicating the platform of the runtime making the event submission. The OS is enumerated by a value indicating the operating system of the runtime making the event submission. The version and os_type fields are freeform strings. For example, on a Windows host, version might be set to “Windows Server 2019”. On a Linux host, version might be set to “5.2” (indicating the kernel version). The os_type on a Linux host might be sourced from the content of lsb_release and might contain “Ubuntu 18.04”, for example. The runtime will calculate the amount of time spent during component startup and report this in the start_time and start_time_us fields. This time represents the overhead induced by the platform during launch.
Another type of event is a component exit event. A component exit event is sent when the component exits (terminates). Component exit events are sent if the component calls exit(3) or abort(3), and may also be sent during other abnormal exit conditions (if these conditions are visible to the runtime). Component exit events have no event parameters or data other than the event envelope.
Another event type is a file event. A file event is sent when various file operations (e.g., open/close/read/write) occur. These are sent for individual operations, when the runtime is in maximum telemetry collection mode. No events are sent on other file operations. File open operations are used to discern component file I/O intent-based on the O_xxx flags to open(2), events may or may not be sent. Exec operations, while not specifically based on open(2), can be sent for components that call exec(3) using a process event.
Yet another event type is a bulk file event. A bulk file event can be sent periodically when the runtime is in minimal telemetry collection mode or higher. It can contains a list of files opened plus the count of each open (e.g., “opened/etc/passwd 10 times”). Multiple files can be contained in a bulk file event.
Network events are yet another event type. Network events can be sent when various network operations (e.g., listen/accept/bind) occur. These are sent for individual operations, when the runtime is in maximum telemetry collection mode. Network events can be sent under the following conditions: inbound connections and outbound connections. An inbound connection event can be sent when the component issues a system call (e.g., the bind(2) system call). Outbound Connections—An outbound connection event can be sent when the component issues a connect system call (e.g., connect(2) system call).
The runtime will fill a NetworkEventBody message with the fields defined above. Protocol numbers are taken from a socket system call (e.g., socket(2) system call) and defined in various protocols. The TIAP portal or command line interface is responsible for converting the protocol numbers to readable strings. Address family information is also taken from a system call (e.g., system(2) call) and correspond to AF_* values from socket.h. The local_address and remote_address fields contain up to 16 bytes of local and remote address information (to accommodate large address types such as IPv6). If shorter address sizes are used, the unused bytes are undefined. It should be noted that all fields are populated on a best-effort basis. In certain circumstances, it is not possible for the runtime to detect some of the parameters required. In this case, the runtime will not supply any value for that field (and the field will default to protobuf's default value for that field type).
Bulk network events are yet another type of telemetry events. Bulk network events can be sent periodically when the runtime is in minimal telemetry collection mode or higher. These events can contain a list of 5-tuple network connection events (e.g., connect from local 1.2.3.4:50 TCP to 4.5.6.7:80). Multiple 5-tuple network connection events can be contained in a bulk network event.
Network change events are another example of telemetry events. Network change evens can be sent when an IP address on the machine changes. This event is also sent by the runtime during component start to let the management portal know which IP addresses the system is currently using. Network change events are sent by the runtime when an network change has been detected on the host. This is a periodic/best-effort message and these events may not be delivered immediately upon network state change. Network changes can include addition or removal of an interface, addition or removal of an IP address to an existing interface, or an alteration of a network's media type. A network change event summarizes the current state of all interfaces on the host. This simplifies the logic required by the API and analytics service as only the latest network change event needs to be examined in order to determine the current state, with the slight drawback of having to re-send information for unchanged interfaces.
Memory events are another example of telemetry events. Memory events can be sent when various memory operations (e.g., mprotect/mmap with unsafe permissions) occur. Memory events can be sent when a component attempts to assign an invalid permission to a region of memory. For example, the event may be sent when attempting to set writable and executable memory simultaneously or attempting to set writable permission on code pages. Memory events are not sent for ‘normal’ memory operations like malloc(2) or free(2). This is due to the volume of ordinary memory events that occur with great frequency during normal component operation.
Depending on the type of memory event, the runtime may or may not be able to compute values for all the fields described above. In this case, the default protobuf values for those data types can be used.
Process events are another example of telemetry type. Process events can be sent when process related operations such as fork/exec or library loads occur. The runtime sends a process event when any of the following occur: the process forks using a fork call (e.g., fork(2)), the process executes using any of the exec*(2) or posix_spawn(2) system calls, or the process loads a new library using a open system call (e.g., dlopen(2)). A process event contains an identifier corresponding to the type of event that occurred, with additional information for execute and library load events.
The info field contains value data if event_type is ExecEvent or LibraryEvent. It is undefined for ForkEvent style process events. The info field contains the name of the executed process plus command line parameters for ExecEvent events, and the fully qualified pathname for LibraryEvent events.
Metadata events are another example of a telemetry type. Metadata events can be sent at periodic intervals to update the management portal with information about memory and CPU usage. Metadata events are periodic events sent from the runtime that contain metrics that are counted by the runtime but that might not necessarily result in alerts being generated. Generally, metadata events are events that contain data that do not fit into other event categories. These metrics can include current process memory usage, current OS-reported CPU usage, number of signals received by the process, TIPA runtime overhead (CPU/memory), and total number of events sent to the event service.
It should be understood that the foregoing IDL definitions are not exhaustive and that other event IDL definitions are possible based on telemetry gathered using embodiments discussed herein.
Third party API usage events are another telemetry type and can be sent when the component makes use of a monitored third party API (e.g., typically CSP-provided APIs, like S3, RDS, etc).
TIAP 700 can be implemented as a multitenant SaaS service. This service contains all the TIAP platform software components. It is anticipated that some customers may desire to host parts or all of the SaaS portal in their own datacentre. To that end, a single-tenant version of the TIAP portal services can be made available as appliance virtual machine images. For example, the appliance image can be an .OVF file for deployment on a local hypervisor (for example, VMware vSphere, Microsoft Hyper-V, or equivalent), or as an Amazon Web Service Amazon Machine Image (AMI). The appliance images are periodically updated and each deployed appliance can optionally be configured to periodically check for updated appliance code.
API service 736 can implement a core set of APIs used by consumers of TIAP 700. For example, API service may enable user interface 722, a command line application tool, or any customer-written applications that interface with TIAP 700. In some embodiments, API service 736 may function as an API server. API service 736 can be in Node.js using a Sail JS MVC framework. Services provided by API service 736 can be implemented as REST APIs and manage many different types of entities stored in an event database (e.g., clickhouse 742). One such entity can include applications, where service 736 retrieves application information from a primary DB (database 744) based on various parameters (application name, for example). Another entity can be components in which server 736 retrieves component group information from the primary DB (database 744) based on various parameters (component ID, for example). Yet another entity can include instances in which service 736 retrieves instance information from the primary DB (database 744) based on various parameters (component ID and hostname, for example). Another entity can include events in which service 736 retrieves event information from the Events DB (ClickHouse 742) based on various parameters (component or application ID plus event type, for example).
API service 736 can also provide REST APIs to manage alert and insight entities stored in an analytics database (not shown). An alert entity API can retrieve alerts that have been deposited by analytics service 737 into an analytics database (not shown). An insight API can retrieve insights (analysis items) that have been generated by analytics service 737.
API service 736 can also provide REST APIs to manage the entities stored in a CVE database. A CVE API can produce a list of CVEs of components that are vulnerable.
API service 736 can provide provides REST APIs to manage the entities stored in a user database. A users API can provide user accounts, including saved thresholds and filters, and other UI settings. A role API can provide group roles, including role permissions.
REST calls to API service 736 can require an API key. API keys are JWTs (JSON Web Tokens) that grant access to the bearer for a particular amount of time. JWTs generated by the API keys are assigned by the authentication service during logon (for the browser/UI based application) and can also be manually created for use with the CLI (users may do this in ‘Account Settings’ in the UI). If desired, the generation of the JWTs can be performed elsewhere as is known in the art. In addition to the UI and the CLI tool, customers may develop their own applications that interface with the platform. In these scenarios, a “push” or “callback” model is used with the customer's API client (e.g., the application the customer is developing). API service 736 allows for a customer-supplied REST endpoint URL to be registered, along with a filter describing which events the customer's application has interest in. When events of these types are generated, the API server will make a REST PUT request to the customer's endpoint with the event data matching the filter supplied. To safeguard against misconfiguration or slow endpoints causing a potential DoS, successive failures or slow callbacks will result in the callback being removed from the API server, and a log message will be generated in the system log. The API server will also rate limit registration requests. API clients written in this fashion may de-register at any time using the same URL they registered with using the API server's de-registration API. Any registered API client may also be de-registered in the UI (XXX—Where?) or via the CLI tool.
Event Service 734 collects event telemetry from components 710. As explained above, each component has been instrumented to supply telemetry event information to TIAP 700. Upon receiving an event (or multiple events), event service 734 converts the event body into a record that is placed into the Events DB on the ClickHouse 742. Event service 734 can receive events via the Internet.
Analytics Service 737 can periodically survey the events collected by event service 734 and stored in the Events DB and attempts to gather insights based on the events that have been collected. Analytics service 737 is responsible for producing all alerts in the platform, as well as any suggested/remedial corrective tasks. Analytics service 737 gathers events and performs analysis on a continual basis. Analytics service 737 can apply grammars to the collected events to determine whether an alert should be generated. Analytics service 737 can also apply various machine learning models to determine if a pattern of events is detected, and whether this pattern should be alerted. Any insight or alerts that are generated can be stored as a record in the analytics DB (e.g., Postgres 744). The analytics DB is queried by API service 736 when determining if an alert or insight is to be rendered to clients.
CVE Service 740 identifies which CVEs the components have known vulnerabilities 741. CVE service 740 can include CVEs that are created and maintained by TIAP 700. CVE service 740 can use a CVE database, which can be populated from a CVE pack. For example, the CVE database may include a snapshot or copy of various CVE databases that is updated on demand or at regular intervals. CVE service 740 can retrieve a list of CVEs from the CVE database. CVE service 740 periodically scans the event database and determines if any components are vulnerable to CVE. The CVE packs (database dumps) can be created manually by staff operating TIAP 700. This is a manual effort since CVE information is not released/published in a fashion that can be automatically queried. CVE susceptibility can be displayed in a UI hierarchy (e.g., CVE susceptibility is shown based on whatever view is currently active in the UI).
A housekeeping service (not shown) periodically performs cleanup of old data that is no longer required, including audit log data (after archival has been performed or at customer request), old telemetry events (retention time is per-customer specific), old alerts/insights (retention time is per-customer specific), and user accounts that have expired from any linked directory services.
Drift service 760 can keep track of instances/processes in combination with other services (e.g., alert service 732, event service 734, CVE service 740) from one build to another to enable a drift policy.
TIAP 700 can maintain several databases in databases 744. An event database can contain all the telemetry received from all loaded applications/components, for all customers. The data in the events database is deposited by the event service and queried by the analytics, CVE, API, and blueprinting services. An insights/alerts database can contain all alerts and insights discovered by the analytics service, as it periodically analyzes data in the events database. Insights/alerts are deposited into the database along with information identifying which component instance (or application) the alert/insight pertains to. An audit log database contains a record of all platform actions performed by a user, for all users in a customer. These entries are generated by the API service as auditable events (changes, etc.) are made using any API offered by the API service. This also includes login/log out events and user profile related events (password changes, etc.). A user database contains information about local users defined for a tenant that are known to the platform. The user database also stores API tokens generated by users that are used by the API service for authentication. A configuration database stores any per-customer configuration information not previously described. This includes any information relating to third party integrations. The configuration database also stores portal-wide configuration used by TIAP systems administrators/operations teams.
Analytics service 800 can report insights into application component behavior that deviates from the norm of other similar components. For example, consider an application consisting of 100 identical components (such a configuration is not uncommon in a large microservice-based application). If analytics service 800 determines that an instance suddenly is behaving differently (increased CPU or memory usage, or network traffic) but still is adhering to a security policy or has not triggered an alert, this variance can be reported to the customer in the TIAP portal user interface. Analytics service 800 continually monitors the event telemetry database, and makes periodic decisions as to if an alert or insight is warranted. These decisions are made based on rules defined in the analytics service. Some rules are built into the TIAP portal (such as the standard rules), while others can be customer defined.
Telemetry 810 defines the events that are monitored and collected at the customer's application. Telemetry events have been discussed above and can include standard telemetry grammars and customer generated telemetry grammars. Analytics server 800 may be made aware of which telemetry events are being collected so that it is better able to analyze the collected events. The telemetry events can include, for example, file activity (e.g., what files did the application modify? when? how often did the modifications occur?), network activity (e.g., which hosts did the application accept network requests from? what was the bandwidth of data transferred during those requests? which hosts did the application make outbound connections to?), process activity (e.g., did the application launch any unknown or untrusted processes?), library usage (e.g., what libraries are being used by the application? what is their provenance? are there known security vulnerabilities in the libraries that are being used?), Use of 3rd party APIs—(e.g, is the application accessing 3rd party APIs (such as cloud service provider (CSP) APIs)?, which resources are accessed by the application? are these accesses approved?), and memory activity (e.g., is the application using memory protection in a safe way?). This illustrative list of telemetry events is merely small sample of a much larger set of telemetries that can be collected.
Topology telemetry 812 can capture application composition and topology by monitoring interactions between components of that application. As explained above, an application is composed of several components, and each component is instrumented or loaded so that each instance of each component operation can be monitored and collected. Since components represent the smallest monitorable piece of an application, the TIAP platform's ability to monitor each component enables analytics service 800 the ability to analyze the application as a whole. Moreover, because any given component is typically a single executable or piece of business logic, such as a microservice, or a web server, or a database, the TIAP platform discussed herein is able to assess the application in a very comprehensive manner. Topology telemetry 812 is able to correlate interactions between components on the backend by analyzing the collected events. This is in contrast with a runtime telemetry that was previously programmed into a telemetry grammar to monitor interactions between the components. For example, topology telemetry 812 may be able to track interactions between application components based typically on IP addresses of hosts running those components. Topology telemetry 812 can be used to assess geographical construction of an application (using GeoIP, if possible). This can provide an additional set of data points when determining the behavior of an application (e.g., which geographies is an application's components communicating with, and are those geographies permissible for the application's current configuration?). If GeoIP information is not available, or unreliable for the specific component in question, the TIAP runtime can query the CSP's instance metadata document to determine in which geography the component is running.
Metrics 814 can define certain metrics that are measured during event telemetry. Metrics are a measurement of a specific quantity or value, observed at a given moment in time. Taken as a collection, metrics can be used to create a trend. Trend lines or graphs are visually represented in the user interface of the TIAP portal. Customers can optionally set a threshold for a trend or metric of interest (for example, alert if the trend of file operations per hour exceeds some preset value). For example, a filesystem metric measures the number of file operations (reads, writes, opens, etc.) per second. It also measures the amount of write I/O that is being performed. As another example, the network metric can measure the number of inbound and outbound connections per second, and bandwidth usage. Metrics for any telemetry can be collected. These metrics can be defined in a metric grammar.
Suggested Corrective Measures 816 is responsible for providing suggestions to improve operation of the application. As event telemetry is collected, it is possible that an application may upload an event that represents a deviation from the expected application behavior. Each deviance from the expected application behavior can generate an alert by alerts 818. Suggestive corrective measure 816 can assess the root cause of the alert and provide a recommendation for fixing it. As events are collected over time, the suggested corrective measures 816 can formulate other suggested changes, for situations that might not warrant an alert. For example, observing application behavior can lead the analytics engine to determine that the order of certain operations is vulnerable to TOCTTOU (time of check to time of use) race conditions. Another example of an insight that analytics service 800 can discern is unsafe use of various system calls (such as mmap/madvise) or changes in the number of system calls issued by or signals received by the application over some set time period. Such information can be presented by suggested corrective measures 816 as non-critical suggested corrective measures or suggested optimization opportunities.
Alerts 818 can define conditions or rules that merit an alert when event telemetries satisfy the rules or conditions. The alert conditions can be predefined a standard set of alerts. The alert conditions can be defined by the customer. In addition, the alerts conditions can be derived from machine learning. The alerts can be categorized according to different levels of alert. For example, there may be four levels of alert, each representing a different degree of severity. Each alert may be labeled according to its level and displayed accordingly in the UI portal. Alerts can be defined by alert grammars that instruct analytics service 800 on how an alert can be recognized, and what the corrective measure there is for that alert (if any). For example, an alert grammar might be described as:
IF MEMORY_PERMISSION=WX OR MEMORY_PERMISSION=RWX THEN ALERT WITH “Dangerous memory permission (writable+executable) used” where MEMORY_PERMISSION is a telemetry event measurement collected by the platform runtime. Note that this is an example grammar to illustrate the concept and is not representative of the real syntax. Alert grammars contain triggers based on metrics, themselves defined by metric grammars. Similar to telemetry and metric grammars, alert grammers are customizable and customer-specific, provisioned from a base set of default grammars.
Insights 820 can define conditions that indicate a potential issue that is identified but does not rise to the level an alert. For example, an insight can be identified when a sudden change occurs with respect to a historical baseline. Insights can be defined with insight grammars, including a standard set of insight grammars and a customer set of insight grammars.
Protection Domain 822 can define high level groupings of events, alerts, metrics, and insights. Protection domains include application operations such as file path access, process execution, network activity, library usage, memory usage, and third party APIs. These Protection domains are abstractions of telemetry events defined by grammars. Such protection domains can be included in a standard set of protection domain grammars. If desired, the customer may customize, delete, or create new protection domains of their own.
SBOM/Vulnerabilities 824 can define components that are included in the application, components that are used by the application, components that are vulnerable, and vulnerable components that are prioritized as having alert status.
Drift policy 826 can define what elements of an application or how the application is accessed or used are to be compared as part of a drift analysis. The policy can be defined by a user or can be predefined.
The user interface is the primary way in which users interact with the TIAP portal (e.g., portal 730). The UI components can be delivered to the client web browser using an nginx server, which is part of the SaaS backend or appliance. The UI components can be rendered using React locally in the client browser, and interactions with the TIAP portal can be done using a REST-based API exposed by the API service. The user interface may embody several design philosophies. For example, standard views may be provided across multiple levels in the application hierarchy. This ensure that the view remains consistent regardless of what level of the application/component/instance hierarchy is being presented. A time range window can be persistent to enable the user the ability to restrict the current data being presented by start and end times. The UI can include filters to enable user to filter the data being shown (using tags applied to components). For example, a user may choose to filter out all “development” components and only show “production” components by creating suitable filters representing the desired view.
The UI may embody a “drill-down” concept. That is, starting at the highest level, a user may continuously refine their view to embody just what they want to see (via filtering, selecting applications/component groups/instances, and selecting timeline views). The UI can remain as consistent as possible during this refinement. The current level in the hierarchy can be shown to the user with a “breadcrumb” list of previous levels at the top of each view. For example: Dashboard->My App1->Databases->MySQL DB 7. The levels in the breadcrumb are be clickable, allowing users to navigate up the hierarchy as needed. The UI may use several different frameworks, libraries, and components.
Panel 1030 may specify various security alerts related to the application. Panel 1030 can specify the total number of alerts 1031 and a per priority breakdown of those alerts 1032. A more detailed breakdown of the alerts is shown in sub-panel 1033, which shows alert level 1034, alert type 1035, name of the alert 1036, and component 1037 corresponding to the alert.
Application view 1000 may also show an application world map that shows the composition of an application based on geography (where the components comprising the application are deployed). This can be visually represented in the browser by a map of the world with icons and counts indicating where components are deployed.
From application view 1000, a user may select a component group (a group of one or more components) for a further “drill-down” view into the events applicable only for that component group (this action transforms the application view into the component view).
The UI instance view (not shown) shows the relevant metrics and trends for a single component instance. This may be the terminal view for the “drill-down” dashboard/application/component group/instance hierarchy.
The user can select any of the panel names in panel 1110 to view more details related to that selected panel. For example, if the user selects network in penal 1110, the UI may display screen 1200 of
If the user selects one of the alerts, screen 1650 of
The UI may present a settings/configurations view that allows for per-customer customization settings. These settings can include a List of current platform components and versions, auto update opt-in/out, user management, and other per-customer settings.
The UI may present an integrations view for defining settings for third-party integrations used by the TIAP. For example, the TIAP can be used in combination with Slack or PagerDuty for receiving alert information when alerts are generated by the analytics service.
The UI may present an account information view for providing per-customer-user account information (e.g., username, password, role configuration, etc.). The account information view can also be used to generate API tokens (JWTs that can be used by customers to interact with the TIAP the CLI tool or applications they have built themselves).
The UI may provide a download icon that enable the user to download a ‘keyed’ command line tool to the user via the browser. The ‘keying’ mechanism means that each loader only communicates to the appliance that created it (thus removing the need to specify an additional “where is my appliance” command line parameter when using the tool). This ‘keying’ is accomplished by linking several .o files present in the appliance along with a generated .c/.o file containing the URL and certificate info for the appliance the assembly is being performed on. Creation of the command line tool takes place on an as-needed basis (generally during initial appliance provisioning, after updating the appliance software's version, or after a hostname change). The downloaded command line tool can be used by developers and operations teams during development and test phases, or it can be placed into the CI/CD build pipeline, performing the loading step as the last step in the build process.
At step 1740, the call is trampolined to the native library after collecting the telemetry event to enable the application to perform the call as originally intended. The interception library can include at least one loaded component corresponding to a respective counterpart component included in the native library, wherein each loaded component is operative to collect the parameters of a call and initiate trampolining of that call to the respective counterpart component in the native library. At step 1750, the telemetry event is transmitted to a TIAP portal. In some embodiments, several collected telemetry events can be batch transmitted to the TIAP portal.
It should be understood that the steps shown in
It should be understood that the steps shown in
At step 1920, the telemetry events can be analyzed to generate a plurality of analytics outputs for display in a user interface based on analysis of the telemetry events. As discussed above in connection with
At step 1930, commands received via the user interface are processed to cause the TIAP system to perform a desired operation, including commands that control how the plurality of analytics outputs are displayed. The UI is configured to display information in a hierarchical format ranging from a top-level view to a bottom-level view, with at least one middle-level view presented therebetween. The top-level view includes a dashboard (e.g.,
It should be understood that the steps shown in
The TIAP runtime gathers information about the application's composition and sends it to the TIAP portal. This is done variously: 1) when the application starts, a list of all packages installed on the customer computer system is uploaded to the TIAP portal (e.g., to facilitate bill of materials listing); 2) when the application starts, a list of all libraries loaded by the application (at start) is uploaded to the TIAP portal. The libraries in the list can be used to determine which of the packages listed in the part I are actually used; and 3) when the application manually loads a library sometime after starting, that library name is uploaded to the TIAP portal. For certain languages, the TIAP runtime sends a list of actually-called functions/methods (e.g., more detailed usage information than just “library foo was loaded”). These called functions/methods can be obtained as part of language specific method/function tracing where the TIAP runtime can intercept every method or function for every class invoked during a program run. This intercept is similar to the library intercept described above. The TIAP runtime may be provided with language specific interception functions (examples of which are discussed below). This information is also periodically uploaded to the TIAP portal. The TIAP runtime can also collect information about each environment's installed packages (e.g., what version of what library was used, etc.) as pass this information to the TIAP portal as dependency information or package information telemetry events.
As explained above, the TIAP system provides a unique insight into the actual code usage patterns of an application by intercepting, at the API level, all functions or methods called in a code module. This information, which can be referred to herein as usage data or telemetry data, provides a map of which functions are used (and where they are called from). This tracing of application usage patterns is performed variously, depending on the programming language of the application being evaluated. For example, different implementations may be used for Java, Python, and C/C++.
For Java applications, a code rewriter is used that inserts a callback to the TIAP runtime for each method defined in a class loaded by the Java Virtual Machine (JVM). This lets the TIAP runtime know which methods are called and which are not. This can be accomplished using a Java agent library that registers for notification each time a class's bytecode is loaded into the JVM. The TIAP Java language specific agent code then rewrites each method's bytecode in the class and inserts additional code at the start of the method. The TIAP Java code can determine wither a particular method been called at least once. If the determination is YES, the original method code is invoked. This ensures that overhead associated with instrumentation is only called once per method. An alternative approach, without loss of generality, would be to remove the determination check as to whether the method has been called and keep track of the number of times each method is called.
If the determination that the particular method has not been called, a “method invoked event” can be sent to the TIAP portal for subsequent display to the user in the user interface. The “method invoked event” can include the name of the JAR (package file), class name (e.g., com.deepfactor.foo.Bar), and the name of the method being called.
For Python applications, a custom tracing module can be loaded during application startup, which calls back into the TIAP runtime for every line of Python code used. This information is consolidated in the TIAP portal and a list of functions/modules/objects that are called is created. The information sent to the TIAP portal is similar in nature to the Java method invoked event.
For compiled (C/C++) code, the system call mincore is used to determine if the page of memory containing the function in question has been loaded into memory by the operating system. This is relatively coarse-grained way of determining which functions may have been called and can potentially suffer from the side effect of possibly overestimating the list of called functions. This approach indicates which functions have not been called. For this embodiment, the information sent to the TIAP portal differs slightly from the type of information sent in the Python and Java cases. Periodically, the following process is used to discover which functions have been called for applications implemented with C or C++.
A map of the process's .text section is performed, to gather a list of text (code) pages present in the application. This can be done via inspecting the ELF header of the process or by reading/proc/XXX/maps (where XXX is the process ID of the application) on Linux. Starting at the beginning of the .text segment, at PAGE_SIZE (eg, 4 KB) intervals, mincore is called to determine if that page has been demand-paged in by the operating system to memory, indicating the page has been accessed. For .text pages, this can typically indicate execution (but could be a read operation, for example, if the process reads its own .text to determine if tampering has occurred). A bitmap of “accessed” versus “not accessed”.text pages is sent to the TIAP portal. This bitmap uses a “1” to indicate a page was accessed and a “0” to indicate that the page was not accessed. After the TIAP portal ingests the bitmap, symbol files present in the TIAP portal (if uploaded by the user) can be used to match each “1” and “0” in the bitmap to a list of functions present on given .text pages at those offsets, yielding a list of functions that “might have been accessed” and a list of functions that “definitively have not been accessed”
Regardless of the software code being used for a given application, the TIAP runtime can provide telemetry data to the TIAP portal. This telemetry data can enable the TIAP portal to display a list of functions or methods that were called and how often such functions and methods were called. Based on the telemetry information, the TIAP portal can assign a risk score or risk rating for a given CVE based on the percentage of code coverage for a given module containing that CVE.
The TIAP portal can perform a usage based correlation based on observations on the application to inform the user whether use of a particular component has made the user vulnerable to a particular CVE. Consider the following example in which a CVE was recently published to reflect a vulnerability in a Java library, but only if certain methods/classes were used in that library. Using the TIAP runtime, which include library intercepts (and language specific agents, discussed below), it is known whether a user used method X or method Y in a particular class. Armed with this knowledge, a security team can prioritize vulnerability mitigation, as if it is proven that the user did use method X or Y, then the corollary is that the user is vulnerable to the CVE.
However, the ability to establish correlations between CVEs and use of applications is difficult, for several reasons. First, there is no programmatic way to automatically know whether a given function is the faulty function from a CVE (in a generic way). Some CVEs are written to be quite vague and do not have function information, and the exact vulnerability information is not available in any form. Such CVEs typically do not include remediation information and typically suggest “upgrading to the next version.” Even those that do only offer that information in a free-form text format such as a paragraph describing the vulnerability and perhaps a passing mention of the function name. Second, there is no easy automated way to scan CVE free-form text to determine what method(s) or code sequences cause the vulnerability. This is because CVE text is freeform, and there is no uniform way to express that information. Vulnerability reporting embodiments discussed herein improve the current state of the art (“you loaded a library from package foo, and package foo has a CVE”) to something with more insight (“you loaded library libfoo.so from package foo (package foo has a CVE) at line 27 of your code from file myapp.c, and then you proceeded to use the following 27 functions from that library, and you didn't use 1982 other functions from libfoo.so”).
In some embodiments, a CVE can include an extension known as a vulnerability exploitability exchange (VEX) extension. VEX provides a machine readable format where the CVE vendor can optionally provide more information to enable tools such as the TIAP to programmatically determine the vulnerability status. For example, the VEX may specify whether a software product is affected by a vulnerability. The TIAP may evaluate VEX extensions of CVEs to determine whether the user's application is affected by a vulnerability.
Given the limitations of CVE reporting, the TIAP portal can provide more useful information than conventional systems. Conventional systems can may merely inform a user that the user has this dependency and there is a CVE logged against it. In contrast, the TIAP system can, for example, inform a user that the user has this dependency, and there is a CVE logged against it, and the user used 45.6% of the functionality of that library in the user's code. This is an example of usage based correlation.
For example, consider the scenario shown in
At step 2430, the CVE service can analyze the received collected data in conjunction with the CVEs to generate a list of vulnerable components used by the application. At step 2440, the CVE service can leverage usage information pertaining to methods invoked and classes loaded to provide additional insight (e.g., statistical analysis) as to the extent a particular component is vulnerable. For example, the CVE service can rank the components according to a vulnerability level or based on user preferences. As a specific example, the components can be ranked according to the vulnerability level regardless of usage, most usage relative to the vulnerability level, or most usage regardless of the vulnerability level.
At step 2450, for CVEs that have VEX extensions, the CVE service can further incorporate the VEX extension information into its analysis of whether a component is vulnerable or not-vulnerable. The VEX extension information may further influence where a particular component is ranked within a ranking of vulnerable components.
At step 2455, the TIAP portal can display the components in a ranked order as determined by the CVE service (e.g., as shown in
It should be understood that the steps shown in
One or more application programming interfaces (“APIs”) may be used in some embodiments (e.g., with respect to system 100, system 700, or any other suitable module or any other suitable portion of such systems of
The drift policy can enable many different types of drift reports to be generated for a user of TIAP. The TIAP can collect telemetry events from instrumented applications and produces alerts and insights based on that telemetry. Typically, the TIAP tracks telemetry and insights for each application separately. User interface navigation in the TIAP offers a way for users to view the data associated with specific applications. Depending on the alert policy in place at the time the telemetry was gathered, different alerts can be generated for a specific application. Typically, each build of an application may generate a set of telemetry, resulting in different alerts per build (and per policy in use at the time those builds were made). The drift service (e.g., drift service 760) can perform drift analysis by comparing a set of drift policy elements telemetry of two or more builds (e.g., two or more sets of telemetry/alerts). Drift analysis provides the ability to compare a set of builds and determine when or where a specific security vulnerability was introduced.
A drift policy can describe the desired drift policy elements (e.g., telemetry or alert classes) to be compared. Drift policies can be defined and saved in the TIAP user interface. For example, a drift policy can be defined to compare all file operation related alerts, or SBOM content, or network accesses, etc. for one or more application builds. If desired, a drift policy can be applied to hypothetical drift policy elements (e.g., telemetry and/or alert data) to generate a hypothetical drift report.
A drift report can be created based on a drift policy applied to one or more application builds and be displayed on the TIAP user interface. The drift report can contain a listing of items defined in the drift policy that changed between builds. Hypothetical or “what if” drift reports can be generated by retroactively applying a different alert policy to an existing set of telemetry associated with an application build. This may produce a different set of alerts, based on the changed alert policy. With drift policies, drift reports, and hypothetical reports available in the TIAP, users can observe in what build was a security vulnerability introduced, whether builds have been improving in security over time (e.g., based on one or more metrics), and whether a change made to a security policy would have affected a security posture of the application (e.g., over time).
At step 2630, process 2600 can receive, at the TIAP portal, CVEs from CVE sources and step 2640, can analyze, with a CVE service, the received telemetry events and the received usage events in conjunction with the CVEs to generate a list of vulnerable components used by the application. At step 2650, the CVE service can use the usage information pertaining to methods invoked and classes loaded to provide analysis indicating an extent a particular component is vulnerable.
At step 2660, process 2600 can display, by the TIAP portal, the vulnerable components in a ranked order as determined by the CVE service, wherein the populated information categories are displayed in conjunction with a respective vulnerable component. Displaying the populated information along with each vulnerable component further enables a user to make more efficient decisions on whether to remediate the component. The user may select a displayed component, and in response to selection of the displayed component, additional information pertaining to that selected component may be displayed.
It should be understood that the steps shown in
It should be understood that the steps shown in
Knowing which file(s) are opened by a scripting language interpreter can facilitate correlating CVEs with dependency packages (NPM modules, Ruby gems, Python modules, etc). This correlation can then be used by the TIAP to provide usage based correlation and the ability to conclusively determine if a piece of software is susceptible to a vulnerability in a third party component. This can be accomplished by determining a list of candidate processes to monitor (e.g., the scripting language interpreter processes, monitoring when the candidate processes open files, and creating a list of file pathnames. Monitoring which files are opened can be done in a variety of ways. For example, the TIAP runtime can perform a system call interception, library call interception, kernel instrumentation, etc. to create a catalog of opened files or file pathnames. After the catalog of opened files is obtained, the TIPA can create a list of dependencies directly referenced by the application. For example, in the case of Node.js programs, the TIAP can choose to enumerate the content of package.json or package-lock.json files, as these files contain a list of the constituent Node.js packages used by the application. The creation of the dependency list can be done by an external “scan” tool which can be pointed at either a source code repository (“source code tree”), at a container image containing artifacts of the built application, or at a “raw” filesystem containing such code. The list of dependencies created can enumerate dependency package names and versions. The specific way in which enumeration is performed is implementation-specific; several such methods are described below.
In one approach, the TIAP can choose to read dependency names and versions directly from cataloge files (package.json/package-lock.json, etc). Alternatively, the TIAP can alternately choose to compute cryptographic hashes of source files (e.g., SHA256) and calculate the package names/versions based upon looking up these hashes in a known list of components. When package names and versions are known, this information can be used to query known vulnerability databases (NIST CVD, etc.) to determine if any of the packages deployed with the application contain vulnerabilities, and if so, how severe those vulnerabilities are, based on some ranked score algorithm acceptable to the user (CVSS score, reachability and exploitability metrics, etc.). Either approach can provide the following data: a list of dependency package names and versions, containing the list of files making up those packages; for each of those packages/versions, a list of vulnerabilities applicable to that dependency; and a list of files opened by the application during its run.
The TIAP can correlate, based upon usage, the best remediation prioritization strategy for the user, for any vulnerabilities present. One approach might be implemented as follows. For each file opened by the application, look up which package contains the file. If the package contains vulnerabilities whose severity score is greater than some user-defined “X” value, insert this dependency into the prioritization list based upon its severity score. Various other prioritization strategies can be conceived. For example, a user may wish to treat all vulnerabilities present with the same severity, even if the vulnerability is not used. Or a user may wish to prioritize not on severity score, but rather on some other metric (for example, number of times the file containing the vulnerability was accessed). To facilitate this, a rule engine can be used that provides a way for users to create their own prioritization schemes based on a defined grammar.
An API may allow a developer of an API-calling component, which may be a third party developer, to leverage specified features provided by an API-implementing component. There may be one API-calling component or there may be more than one such component. An API can be a source code interface that a computer system or program library may provide in order to support requests for services from an application. An operating system (“OS”) can have multiple APIs to allow applications running on the OS to call one or more of those APIs, and a service (e.g., a program library) can have multiple APIs to allow an application that uses the service to call one or more of those APIs. An API can be specified in terms of a programming language that can be interpreted or compiled when an application is built.
In some embodiments, the API-implementing component may provide more than one API, each providing a different view of or with different aspects that access different aspects of the functionality implemented by the API-implementing component. For example, one API of an API-implementing component can provide a first set of functions and can be exposed to third party developers, and another API of the API-implementing component can be hidden (e.g., not exposed) and can provide a subset of the first set of functions and can also provide another set of functions, such as testing or debugging functions which are not in the first set of functions. In other embodiments, the API-implementing component may itself call one or more other components via an underlying API and may thus be both an API-calling component and an API-implementing component.
An API may define the language and parameters that API-calling components may use when accessing and using specified features of the API-implementing component. For example, an API-calling component may access the specified features of the API-implementing component through one or more API calls or invocations (e.g., embodied by function or method calls) exposed by the API and may pass data and control information using parameters via the API calls or invocations. The API-implementing component may return a value through the API in response to an API call from an API-calling component. While the API may defines the syntax and result of an API call (e.g., how to invoke the API call and what the API call does), the API may not reveal how the API call accomplishes the function specified by the API call. Various API calls may be transferred via the one or more application programming interfaces between the calling component (e.g., API-calling component) and an API-implementing component. Transferring the API calls may include issuing, initiating, invoking, calling, receiving, returning, and/or responding to the function calls or messages. Thus, transferring can describe actions by either of the API-calling component or the API-implementing component. The function calls or other invocations of the API may send or receive one or more parameters through a parameter list or other structure. A parameter can be a constant, key, data structure, object, object class, variable, data type, pointer, array, list, or a pointer to a function or method or another way to reference a data or other item to be passed via the API.
Furthermore, data types or classes may be provided by the API and implemented by the API-implementing component. Thus, the API-calling component may declare variables, use pointers to, use or instantiate constant values of such types or classes by using definitions provided in the API.
Generally, an API can be used to access a service or data provided by the API-implementing component or to initiate performance of an operation or computation provided by the API-implementing component. By way of example, the API-implementing component and the API-calling component may each be any one of an operating system, a library, a device driver, an API, an application program, or other module. It should be understood that the API-implementing component and the API-calling component may be the same or different type of module from each other. API-implementing components may in some cases be embodied at least in part in firmware, microcode, or other hardware logic. In some embodiments, an API may allow a client program to use the services provided by a Software Development Kit (“SDK”) library. In other embodiments, an application or other client program may use an API provided by an Application Framework. In such embodiments, the application or client program may incorporate calls to functions or methods provided by the SDK and provided by the API or may use data types or objects defined in the SDK and provided by the API. An Application Framework may, in these embodiments, provide a main event loop for a program that responds to various events defined by the Framework. The API may allow the application to specify the events and the responses to the events using the Application Framework. In some implementations, an API call can report to an application the capabilities or state of a hardware device, including those related to aspects such as input capabilities and state, output capabilities and state, processing capability, power state, storage capacity and state, communications capability, and the like, and the API may be implemented in part by firmware, microcode, or other low level logic that may execute in part on the hardware component.
The API-calling component may be a local component (i.e., on the same data processing system as the API-implementing component) or a remote component (i.e., on a different data processing system from the API-implementing component) that may communicate with the API-implementing component through the API over a network. It should be understood that an API-implementing component may also act as an API-calling component (i.e., it may make API calls to an API exposed by a different API-implementing component) and an API-calling component may also act as an API-implementing component by implementing an API that may be exposed to a different API-calling component.
The API may allow multiple API-calling components written in different programming languages to communicate with the API-implementing component, such that the API may include features for translating calls and returns between the API-implementing component and the API-calling component. However, the API may be implemented in terms of a specific programming language. An API-calling component can, in some embodiments, may call APIs from different providers, such as a set of APIs from an OS provider and another set of APIs from a plug-in provider and another set of APIs from another provider (e.g., the provider of a software library) or creator of the another set of APIs.
It is to be appreciated that API-implementing component 2010 may include additional functions, methods, classes, data structures, and/or other features that may not be specified through API 2020 and that may not be available to API-calling component 2030. It is to be understood that API-calling component 2030 may be on the same system as API-implementing component 2010 or may be located remotely and may access API-implementing component 2010 using API 2020 over a network. While
API-implementing component 2010, API 2020, and API-calling component 2030 may each be implemented by software, but may also be implemented in hardware, firmware, or any combination of software, hardware, and firmware. They each may also be embodied as machine- or computer-readable code recorded on a machine- or computer-readable medium. The computer-readable medium may be any data storage device that can store data or instructions which can thereafter be read by a computer system. Examples of the computer-readable medium may include, but are not limited to, read-only memory, random-access memory, flash memory, CD-ROMs, DVDs, magnetic tape, and optical data storage devices (e.g., CRSM 105, one or more non-volatile data storage devices 107, and main memory 108 of
For example, as shown in
In some embodiments, a data processing system may be provided to include a processor to execute instructions, and a memory coupled with the processor to store instructions that, when executed by the processor, may cause the processor to perform operations to generate an API that may allow an API-calling component to perform at least some of the operations of one or more of the processes described with respect to one or more of
Moreover, the processes described with respect to one or more of
It is to be understood that any or each module of any one or more of any system, device, or server may be provided as a software construct, firmware construct, one or more hardware components, or a combination thereof, and may be described in the general context of computer-executable instructions, such as program modules, that may be executed by one or more computers or other devices. Generally, a program module may include one or more routines, programs, objects, components, and/or data structures that may perform one or more particular tasks or that may implement one or more particular abstract data types. It is also to be understood that the number, configuration, functionality, and interconnection of the modules of any one or more of any system device, or server are merely illustrative, and that the number, configuration, functionality, and interconnection of existing modules may be modified or omitted, additional modules may be added, and the interconnection of certain modules may be altered.
While there have been described systems, methods, and computer-readable media for enabling efficient control of a media application at a media electronic device by a user electronic device, it is to be understood that many changes may be made therein without departing from the spirit and scope of the disclosure. Insubstantial changes from the claimed subject matter as viewed by a person with ordinary skill in the art, now known or later devised, are expressly contemplated as being equivalently within the scope of the claims. Therefore, obvious substitutions now or later known to one with ordinary skill in the art are defined to be within the scope of the defined elements.
Therefore, those skilled in the art will appreciate that the invention can be practiced by other than the described embodiments, which are presented for purposes of illustration rather than of limitation.
This application is a continuation-in-part of U.S. patent application Ser. No. 18/159,985, filed Jan. 26, 2023, which claims priority to U.S. Provisional Patent Application No. 63/303,943, filed Jan. 27, 2022, and U.S. patent application Ser. No. 18/159,985 is also a continuation-in-part of U.S. patent application Ser. No. 17/592,891, filed Feb. 4, 2022 (now U.S. Pat. No. 11,620,203), which is a continuation of U.S. patent application Ser. No. 16/938,869, filed Jul. 24, 2020 (now U.S. Pat. No. 11,243,861), which claims the benefit of U.S. Provisional Patent Application No. 62/878,490, filed Jul. 25, 2019 and U.S. Provisional Patent Application No. 62/878,502, filed Jul. 25, 2019. This application claims priority to U.S. Provisional Application No. 63/509,358, filed Jun. 21, 2023, and to U.S. Provisional Application No. 63/509,363, filed Jun. 21, 2023. All disclosures are incorporated herein in their entireties.
| Number | Date | Country | |
|---|---|---|---|
| 63303943 | Jan 2022 | US | |
| 62878490 | Jul 2019 | US | |
| 62878502 | Jul 2019 | US | |
| 63509358 | Jun 2023 | US | |
| 63509363 | Jun 2023 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16938869 | Jul 2020 | US |
| Child | 17592891 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 18159985 | Jan 2023 | US |
| Child | 18669616 | US | |
| Parent | 17592891 | Feb 2022 | US |
| Child | 18159985 | US |
