CVE-2017-7550

What is this vulnerability?

CVE-2017-7550 is categorized as a critical Log Information Exposure flaw with a CVSS base score of 9.8. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

A flaw was found in the way Ansible (2.3.x before 2.3.3, and 2.4.x before 2.4.1) passed certain parameters to the jenkins_plugin module. Remote attackers could use this flaw to expose sensitive information from a remote host's logs. This flaw was fixed by not allowing passwords to be specified in the "params" argument, and noting this in the module documentation.

This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.

Risk Assessment

Impact on Systems

✅ Credential Theft: Exposed secrets enable unauthorized access to infrastructure, cloud services, and third-party integrations.

✅ Compliance Violation: Leaking PII or credentials may violate GDPR, HIPAA, PCI-DSS, and SOC 2 requirements.

✅ Supply Chain Risk: Compromised credentials in public repositories can propagate to downstream consumers.

How to Fix and Mitigate CVE-2017-7550

1. Apply Vendor Patches: Upgrade affected components to their latest, non-vulnerable versions immediately.
2. Implement Input Validation: Ensure all user-supplied data is validated, sanitized, and type-checked before processing.
3. Deploy Runtime Protection: Use Precogs continuous monitoring to detect exploitation attempts in real time.
4. Audit Dependencies: Review and update all third-party libraries and transitive dependencies.

Defending with Precogs AI

Precogs PII & Secrets Scanner automatically identifies hardcoded credentials, exposed API keys, and personally identifiable information leaks across repositories, CI/CD pipelines, and deployed artifacts.

Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.

Start scanning with Precogs →

Vulnerability Code Signature

Attack Data Flow

Vulnerable Code Pattern

# ❌ VULNERABLE: Log Information Exposure
def authenticate(user, password):
    # Taint sink: logging sensitive password
    logger.info(f"User {user} attempting login with password {password}")
    # ... authentication logic ...

Secure Code Pattern

# ✅ SECURE: Sanitized Logging
def authenticate(user, password):
    # Sanitized logging: password omitted
    logger.info(f"User {user} attempting login")
    # ... authentication logic ...

How Precogs Detects This

Precogs PII & Secrets Scanner continuously monitors codebases for insecure logging of sensitive information and PII.