GHSA-2rcg-mm5h-xchx: PraisonAI Agents

## Summary The MentionsParser in `src/praisonai-agents/praisonaiagents/tools/mentions.py` processes `@file:` mentions in agent prompts by reading arbitrary files from the filesystem. When a file path is not found relative to the workspace, the parser falls back to using the path as an absolute...

Full CISO analysis pending enrichment.

What systems are affected?

Package	Ecosystem	Vulnerable Range	Patched
PraisonAI Agents	pip	< 1.6.59	`1.6.59`
11 dependents 81% patched ~0d to patch Full package profile →

Do you use PraisonAI Agents? You're affected.

How severe is it?

CVSS 3.1

7.5 / 10

EPSS

N/A

Exploitation Status

No known exploitation

Sophistication

N/A

What is the attack surface?

AV Network

AC Low

PR None

UI None

S Unchanged

C High

I None

A None

What should I do?

Patch available

Update PraisonAI Agents to version 1.6.59

Which compliance frameworks are affected?

Compliance analysis pending. Sign in for full compliance mapping when available.

Frequently Asked Questions

What is GHSA-2rcg-mm5h-xchx?

## Summary The MentionsParser in `src/praisonai-agents/praisonaiagents/tools/mentions.py` processes `@file:` mentions in agent prompts by reading arbitrary files from the filesystem. When a file path is not found relative to the workspace, the parser falls back to using the path as an absolute path without any validation or boundary check. This allows an attacker who can influence agent prompts (via chat messages, Telegram/Discord/Slack bot inputs, or YAML workflow configs) to read any file on the filesystem accessible to the process user. ## Details **Vulnerable code (lines 165–178):** ```python def _process_file_mention(self, file_path: str) -> Optional[str]: """Process @file:path mention.""" try: # Resolve path relative to workspace full_path = self.workspace_path / file_path if not full_path.exists(): # Try as absolute path full_path = Path(file_path) if not full_path.exists(): self._log(f"File not found: {file_path}", logging.WARNING) return f"# File: {file_path}\n[File not found]" content = full_path.read_text(encoding="utf-8") ``` **The vulnerability is in the fallback at line 171–172:** When the file is not found relative to `workspace_path`, the code constructs `full_path = Path(file_path)`, which accepts any absolute or relative path without validation. There is no: - `..` path traversal check - Workspace boundary validation - Symlink resolution against workspace - Protected path guard The `file_path` parameter originates from parsing `@file:` mentions in user/LLM prompts. The `MentionsParser` is used across the framework to process mentions in agent instructions and user messages. **Contrast with `skill_tools.py` `read_skill_file`** (lines 140–193), which properly validates: ```python # skill_tools.py line 179 — proper validation if os.path.commonpath([full_path, skill_path]) != skill_path: return f"Error: Path traversal detected - {file_path} is outside skill directory" ``` ## PoC **Setup:** Clean checkout at commit `d5f1114a`. **Positive trigger — arbitrary file read via @file: mention:** ```python import sys sys.path.insert(0, 'src/praisonai-agents') from praisonaiagents.tools.mentions import MentionsParser parser = MentionsParser() # Test 1: Absolute path read (bypasses workspace resolution) result = parser._process_file_mention('/etc/hostname') print(f'Absolute path read: {result[:80]}...') # Test 2: Relative path with traversal result = parser._process_file_mention('../../../etc/hostname') print(f'Traversal read: {result[:80]}...') ``` **Expected output:** ``` Absolute path read: # File: /etc/hostname ```linux <hostname> ```... Traversal read: # File: ../../../etc/hostname ```linux <hostname> ```... ``` **Negative control — non-existent file:** ```python result = parser._process_file_mention('/nonexistent/secret.txt') # Returns: "# File: /nonexistent/secret.txt\n[File not found]" ``` **Cleanup:** No persistence or side effects — read-only operation. ## Impact An attacker who can inject `@file:` mentions into agent prompts (via chat messages in Telegram/Discord/Slack bots, user input in web UI, or YAML workflow configurations) can read any file accessible to the process user, including: - **Secrets and credentials:** `.env` files, `~/.aws/credentials`, `~/.ssh/id_rsa`, API keys - **Configuration files:** Database passwords, JWT secrets, OAuth tokens - **Source code:** Application internals, database schemas - **System files:** `/etc/passwd`, `/etc/shadow` (if process has read access) This is particularly dangerous in bot deployments where `auto_approve_tools` defaults to `True` and untrusted users can send messages containing `@file:` mentions. ## Suggested remediation 1. **Remove the absolute path fallback.** Only resolve files within `workspace_path`: ```python def _process_file_mention(self, file_path: str) -> Optional[str]: full_path = (self.workspace_path / file_path).resolve() # Ensure resolved path is within workspace if not str(full_path).startswith(str(self.workspace_path.resolve())): return f"# File: {file_path}\n[Access denied: path outside workspace]" if not full_path.exists(): return f"# File: {file_path}\n[File not found]" content = full_path.read_text(encoding="utf-8") ``` 2. Add symlink resolution via `.resolve()` to prevent symlink-based traversal. 3. Add a protected path guard (`.env`, `.git`, `.ssh`, keys, credentials). 4. Apply the same `os.path.commonpath` pattern used by `skill_tools.py`.

Is GHSA-2rcg-mm5h-xchx actively exploited?

No confirmed active exploitation of GHSA-2rcg-mm5h-xchx has been reported, but organizations should still patch proactively.

How to fix GHSA-2rcg-mm5h-xchx?

Update to patched version: PraisonAI Agents 1.6.59.

What is the CVSS score for GHSA-2rcg-mm5h-xchx?

GHSA-2rcg-mm5h-xchx has a CVSS v3.1 base score of 7.5 (HIGH).

What are the technical details?

Original Advisory

## Summary The MentionsParser in `src/praisonai-agents/praisonaiagents/tools/mentions.py` processes `@file:` mentions in agent prompts by reading arbitrary files from the filesystem. When a file path is not found relative to the workspace, the parser falls back to using the path as an absolute path without any validation or boundary check. This allows an attacker who can influence agent prompts (via chat messages, Telegram/Discord/Slack bot inputs, or YAML workflow configs) to read any file on the filesystem accessible to the process user. ## Details **Vulnerable code (lines 165–178):** ```python def _process_file_mention(self, file_path: str) -> Optional[str]: """Process @file:path mention.""" try: # Resolve path relative to workspace full_path = self.workspace_path / file_path if not full_path.exists(): # Try as absolute path full_path = Path(file_path) if not full_path.exists(): self._log(f"File not found: {file_path}", logging.WARNING) return f"# File: {file_path}\n[File not found]" content = full_path.read_text(encoding="utf-8") ``` **The vulnerability is in the fallback at line 171–172:** When the file is not found relative to `workspace_path`, the code constructs `full_path = Path(file_path)`, which accepts any absolute or relative path without validation. There is no: - `..` path traversal check - Workspace boundary validation - Symlink resolution against workspace - Protected path guard The `file_path` parameter originates from parsing `@file:` mentions in user/LLM prompts. The `MentionsParser` is used across the framework to process mentions in agent instructions and user messages. **Contrast with `skill_tools.py` `read_skill_file`** (lines 140–193), which properly validates: ```python # skill_tools.py line 179 — proper validation if os.path.commonpath([full_path, skill_path]) != skill_path: return f"Error: Path traversal detected - {file_path} is outside skill directory" ``` ## PoC **Setup:** Clean checkout at commit `d5f1114a`. **Positive trigger — arbitrary file read via @file: mention:** ```python import sys sys.path.insert(0, 'src/praisonai-agents') from praisonaiagents.tools.mentions import MentionsParser parser = MentionsParser() # Test 1: Absolute path read (bypasses workspace resolution) result = parser._process_file_mention('/etc/hostname') print(f'Absolute path read: {result[:80]}...') # Test 2: Relative path with traversal result = parser._process_file_mention('../../../etc/hostname') print(f'Traversal read: {result[:80]}...') ``` **Expected output:** ``` Absolute path read: # File: /etc/hostname ```linux <hostname> ```... Traversal read: # File: ../../../etc/hostname ```linux <hostname> ```... ``` **Negative control — non-existent file:** ```python result = parser._process_file_mention('/nonexistent/secret.txt') # Returns: "# File: /nonexistent/secret.txt\n[File not found]" ``` **Cleanup:** No persistence or side effects — read-only operation. ## Impact An attacker who can inject `@file:` mentions into agent prompts (via chat messages in Telegram/Discord/Slack bots, user input in web UI, or YAML workflow configurations) can read any file accessible to the process user, including: - **Secrets and credentials:** `.env` files, `~/.aws/credentials`, `~/.ssh/id_rsa`, API keys - **Configuration files:** Database passwords, JWT secrets, OAuth tokens - **Source code:** Application internals, database schemas - **System files:** `/etc/passwd`, `/etc/shadow` (if process has read access) This is particularly dangerous in bot deployments where `auto_approve_tools` defaults to `True` and untrusted users can send messages containing `@file:` mentions. ## Suggested remediation 1. **Remove the absolute path fallback.** Only resolve files within `workspace_path`: ```python def _process_file_mention(self, file_path: str) -> Optional[str]: full_path = (self.workspace_path / file_path).resolve() # Ensure resolved path is within workspace if not str(full_path).startswith(str(self.workspace_path.resolve())): return f"# File: {file_path}\n[Access denied: path outside workspace]" if not full_path.exists(): return f"# File: {file_path}\n[File not found]" content = full_path.read_text(encoding="utf-8") ``` 2. Add symlink resolution via `.resolve()` to prevent symlink-based traversal. 3. Add a protected path guard (`.env`, `.git`, `.ssh`, keys, credentials). 4. Apply the same `os.path.commonpath` pattern used by `skill_tools.py`.

Weaknesses (CWE)

CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') Primary

CWE-22 — Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'): The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.

[Implementation] Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylis
[Architecture and Design] For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.

Source: MITRE CWE corpus.