aletheia-cyber-core

v1.9.3 suspicious
6.0
Medium Risk

Runtime audit and pre-execution block layer for autonomous AI agents. Protects against instruction smuggling, semantic camouflage, and supply-chain attacks.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential obfuscation and credential risk, which raises concerns about its intentions. While there is no definitive proof of malicious behavior, the combination of these factors warrants further investigation.

  • High obfuscation risk due to base64 decoding
  • Moderate credential risk from accessing sensitive environment variables
Per-check LLM notes
  • Network: The use of httpx for making network requests is common and does not inherently indicate malicious activity.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The presence of base64 decoding with error handling suggests possible obfuscation or encryption, which could be used for malicious purposes.
  • Credentials: The code accessing environment variables like AWS_REGION and the regex patterns indicate potential credential harvesting, but it may also be part of normal functionality such as logging or configuration.
  • Metadata: The author's information is sparse and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://aletheia-core.com
  • Detailed PyPI description (52823 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 276 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in holeyfield33-art/aletheia-core
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • ort httpx async with httpx.AsyncClient(timeout=10) as client: if not self._jwks_uri:
  • httpx async with httpx.AsyncClient(timeout=5) as client: resp = await client.ge
  • list[Any]: async with httpx.AsyncClient(timeout=2.0) as client: resp = await client.post
  • d) self._client = httpx.AsyncClient( base_url=self._url, headers
  • x self._client = httpx.AsyncClient( headers={ "Authorizatio
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • ombinations) try: base64.b64decode(stripped, validate=True) except Exception: retur
  • try: raw = base64.b64decode(m.group(1), validate=True) if len(raw) > policy.
  • : decoded_bytes = base64.b64decode(current, validate=True) except Exception:
  • "Prompt_Injection": re.compile( r"\b(?:system\s+prompt|inject|override|prompt|instructions?|execute|" r"arbitrary|run|shell|code)\b",
  • e.IGNORECASE), re.compile(r"\b(?:socket|exec|subprocess|eval|shell)\b", re.IGNORECASE), ]
  • xecute arbitrary command": re.compile( r"\bexecute\s+(?:arbitrary|any|random|all)\s+command\b", re.IGNORECA
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • ) from exc region = os.environ.get("AWS_REGION", "us-east-1") self._prefix = os.environ.get(
  • (?:\.\./\.\./\.\./)|(?:file:///etc/passwd)|(?:javascript:)|(?:data:text/html)", re.IG
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository holeyfield33-art/aletheia-core appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aletheia-cyber-core 
Develop a secure and autonomous AI agent management system using the 'aletheia-cyber-core' Python package. This system will serve as a runtime environment for AI agents, ensuring they operate securely and without malicious interference. Here are the steps and features to consider:

1. **Setup**: Begin by installing the 'aletheia-cyber-core' package and setting up your development environment.
2. **Agent Registration**: Implement a feature where AI agents can register themselves with the system. Each agent must provide metadata about its capabilities and intended use.
3. **Runtime Audit**: Utilize 'aletheia-cyber-core' to perform real-time audits on registered agents. Ensure that no unauthorized instructions or behaviors are executed.
4. **Pre-Execution Block Layer**: Before any agent executes a task, implement a pre-execution check using 'aletheia-cyber-core'. This should verify the integrity of the task and ensure it aligns with the agent's registered metadata.
5. **Security Alerts**: If any suspicious activity is detected, such as attempts at instruction smuggling or semantic camouflage, trigger security alerts. These alerts should notify administrators and log the details of the suspicious behavior.
6. **Supply-Chain Protection**: Ensure that all updates or new agents added to the system are verified through a secure supply chain process, leveraging 'aletheia-cyber-core' for protection against supply-chain attacks.
7. **User Interface**: Develop a simple web-based UI where administrators can monitor the status of registered agents, view logs, and manage security settings.
8. **Documentation and Testing**: Provide comprehensive documentation detailing how to use the system and the integration of 'aletheia-cyber-core'. Conduct thorough testing to validate the security features and overall functionality.

💬 Discussion Feed

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