Summary
FinRobot v1.0.0 contains a code injection vulnerability in the
CodingUtils.modify_code component. If attacker-controlled input reaches
the code modification workflow and is subsequently executed, an attacker
may influence application behavior or achieve arbitrary code execution.
FinRobot v1.0.0 contains a code injection vulnerability in the
CodingUtils.modify_code component. If attacker-controlled input reaches
the code modification workflow and is subsequently executed, an attacker
may influence application behavior or achieve arbitrary code execution.
Affected context
The vulnerability occurs in deployments using FinRobot v1.0.0 where the
CodingUtils.modify_code functionality processes input that is not fully
trusted. Risk depends on whether modified code is evaluated or executed and
on the privileges available to the FinRobot process.
The vulnerability occurs in deployments using FinRobot v1.0.0 where the
CodingUtils.modify_code functionality processes input that is not fully
trusted. Risk depends on whether modified code is evaluated or executed and
on the privileges available to the FinRobot process.
Exploit preconditions
- Attack surface: The
CodingUtils.modify_codecode-generation or
modification workflow
- Required access: Ability to supply or influence input processed by
that workflow
- Trigger point: Processing and subsequent evaluation or execution of
modified code
- Why exploitation is possible: Input may cross into an executable code
context without sufficient separation, validation, or trust-boundary
enforcement
- Attack surface: The
CodingUtils.modify_codecode-generation or
modification workflow
- Required access: Ability to supply or influence input processed by
that workflow
- Trigger point: Processing and subsequent evaluation or execution of
modified code
- Why exploitation is possible: Input may cross into an executable code
context without sufficient separation, validation, or trust-boundary
enforcement
Why this happens
The underlying issue is an unsafe transition from attacker-influenced data to
executable program logic. This behavior maps to CWE-94: Improper Control of Generation of Code ('Code Injection'), in which application input can
affect generated or modified code that is later interpreted or executed.
The underlying issue is an unsafe transition from attacker-influenced data to
executable program logic. This behavior maps to CWE-94: Improper Control of Generation of Code ('Code Injection'), in which application input can
affect generated or modified code that is later interpreted or executed.
Potential impact
- An attacker may execute unintended code with the privileges of the
FinRobot process.
- Sensitive files, environment variables, or credentials could be exposed.
- Application data or generated artifacts could be altered.
- The affected host or workload could be used for further compromise.
- An attacker may execute unintended code with the privileges of the
FinRobot process.
- Sensitive files, environment variables, or credentials could be exposed.
- Application data or generated artifacts could be altered.
- The affected host or workload could be used for further compromise.
General mitigation guidance
Mitigation generally focuses on preventing untrusted data from becoming
executable code.
Common defensive patterns include:
- Prefer structured operations and fixed code templates over dynamic code
generation or execution.
- Apply strict allowlists and schema validation to inputs that influence code
modifications.
- Separate generated content from executable paths and require explicit,
isolated review before execution.
- Run code-processing workloads with least privilege and restricted access to
secrets, filesystems, and network services.
- Enforce trust boundaries through sandboxing and secure-by-default execution
policies where code execution is necessary.
Mitigation generally focuses on preventing untrusted data from becoming
executable code.
Common defensive patterns include:
- Prefer structured operations and fixed code templates over dynamic code
generation or execution.
- Apply strict allowlists and schema validation to inputs that influence code
modifications.
- Separate generated content from executable paths and require explicit,
isolated review before execution.
- Run code-processing workloads with least privilege and restricted access to
secrets, filesystems, and network services.
- Enforce trust boundaries through sandboxing and secure-by-default execution
policies where code execution is necessary.
How teams detect issues like this
Detection approaches may include:
- Static analysis for dynamic evaluation, runtime compilation, shell execution,
and string concatenation used to construct executable code.
- Code review checks for flows from user-controlled or external inputs into
modify_code and subsequent execution APIs.
- Policy enforcement that blocks unrestricted dynamic code execution in
production workloads.
- Runtime monitoring for unexpected child processes, file changes, or network
activity from FinRobot workers.
- Automated security review tools can help identify input-to-code execution
paths during development.
Detection approaches may include:
- Static analysis for dynamic evaluation, runtime compilation, shell execution,
and string concatenation used to construct executable code.
- Code review checks for flows from user-controlled or external inputs into
modify_code and subsequent execution APIs.
- Policy enforcement that blocks unrestricted dynamic code execution in
production workloads.
- Runtime monitoring for unexpected child processes, file changes, or network
activity from FinRobot workers.
- Automated security review tools can help identify input-to-code execution
paths during development.
Sources
| Source | Link |
|---|---|
| gist. | gist.github.com/ |
| github. | github.com/ |
