Cyber Resilience

CVE-2025-53097

Roocode Roo Code ≤ 3.20.3

Published
27 June 2025
Modified
17 June 2026
Patch / advisory
View advisory
CVSS Score v3.1 5.9
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0043 36th percentile
Risk Priority 46 floored blend · peak EPSS

Summary

CVE-2025-53097 is a medium-severity Injection (CWE-74) vulnerability in Roocode Roo Code. Its CVSS base score is 5.9 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 36th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the LLM/Generative AI Risks risk domain.

The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's `search_files` tool did not respect the setting to disable reads outside of the VS Code workspace. This means that…

more

an attacker who was able to inject a prompt into the agent could potentially read a sensitive file and then write the information to a JSON schema. Users have the option to disable schema fetching in VS Code, but the feature is enabled by default. For users with this feature enabled, writing to the schema would trigger a network request without the user having a chance to deny. This issue is of moderate severity, since it requires the attacker to already be able to submit prompts to the agent. Version 3.20.3 fixed the issue where `search_files` did not respect the setting to limit it to the workspace. This reduces the scope of the damage if an attacker is able to take control of the agent through prompt injection or another vector.

CWE(s)
CWE-74

AI Security AnalysisAI

AI Category
AI Agent Protocols and Integrations
Risk Domain
LLM/Generative AI Risks
OWASP Top 10 for LLMs 2025
LLM01:2025 Prompt Injection
Classification Reason
Matched keywords: ai, prompt injection

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
T1221 Template Injection Stealth
Adversaries may create or modify references in user document templates to conceal malicious code or force authentication attempts.
attack.mitre.org →
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
attack.mitre.org →
T1674 Input Injection Execution
Adversaries may simulate keystrokes on a victim’s computer by various means to perform any type of action on behalf of the user, such as launching the command interpreter using keyboard shortcuts, typing an inline script to be executed,…
attack.mitre.org →
T1059 Command and Scripting Interpreter Execution
Adversaries may abuse command and script interpreters to execute commands, scripts, or binaries.
attack.mitre.org →
T1059.001 PowerShell Execution
Adversaries may abuse PowerShell commands and scripts for execution.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-27022Shared CWE-74
CVE-2026-44246Shared CWE-74
CVE-2023-23749Shared CWE-74
CVE-2023-48835Shared CWE-74
CVE-2023-51939Shared CWE-74
CVE-2023-33242Shared CWE-74
CVE-2023-4157Shared CWE-74
CVE-2024-28191Shared CWE-74
CVE-2022-2992Shared CWE-74
CVE-2024-36420Shared CWE-74

Affected Assets

roocode
roo code
≤ 3.20.3

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.2.1
  • V1.2.3
  • V1.2.5
  • V1.2.8

Mitigating Controls (NIST 800-53 r5) AI

SI-10 Information Input Validation good match

SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly require input validation and output encoding that prevent injection flaws.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.8.29 Security testing in development and acceptance mostly match
finds

Security testing in development catches injection vulnerabilities before release.

A.8.15 Logging partial match
finds

Logging supports detection of injection attempts but does not prevent the weakness.

A.8.16 Monitoring activities partial match
finds

Monitoring activities can identify active injection attacks after they occur.

A.8.25 Secure development life cycle partial match
prevents

Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.

A.8.26 Application security requirements partial match
prevents

Application security requirements explicitly call for controls against injection attacks in software design.

A.8.27 Secure system architecture and engineering principles partial match
prevents

Secure architecture principles reduce injection surfaces but do not prescribe specific neutralization techniques.

References