Server-Side Request Forgery in poco-ai Task Execution

A vulnerability was identified in poco-ai poco-claw up to 0.5.4. This issue affects the function run_task of the file executor/app/api/v1/task.py. The manipulation of the argument callback_url leads to server-side request forgery. The attack is possible to be carried out remotely. The exploit is publicly available and might be used. The reported GitHub issue was closed automatically due to inactivity.

Casky was already ahead

This CVE exploits attack patterns that Casky's 331matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

CVE-2026-16016 is a server-side request forgery (SSRF) vulnerability in poco-ai's poco-claw library affecting versions up to 0.5.4. The flaw exists in the task execution endpoint (executor/app/api/v1/task.py) where the callback_url parameter is insufficiently validated, allowing attackers to manipulate the server into making unauthorized requests to internal or external systems. This vulnerability carries a CVSS score of 7.3 (high severity) and poses a significant risk to organizations using poco-claw for task automation and orchestration, as attackers can leverage it to access internal resources, interact with backend systems, or pivot to other infrastructure components—all without direct network access to those targets.

Casky's 331 mapped skills leverage Claude AI with extended reasoning to detect attack patterns aligned with MITRE ATT&CK techniques TA0001 (Initial Access) and TA0006 (Credential Access). When analyzing network traffic and application logs, practitioners would observe detection of suspicious callback_url manipulation attempts, anomalous outbound connections from the application to unexpected internal IP ranges or cloud metadata services, and reconnaissance patterns typical of SSRF exploitation. Casky's skill set enables practitioners to identify the initial compromise vector, trace lateral movement attempts via forced internal requests, and correlate behavioral indicators—such as repeated requests to localhost or 169.254.x.x addresses—that signal active exploitation of this vulnerability before credential theft or system compromise occurs.

Live Threat IntelligenceComing soon

Casky Risk Score

—

EPSS Probability

—

Shodan Exposure

—

GreyNoise Signal

—

Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

331 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-16016.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

Run

abusing-dpapi-for-credential-access

red teaming · high

Run

abusing-shadow-credentials-for-privesc

red teaming · high

Run

MITRE ATT&CK Techniques

TA0001 TA0006

Investigate the attack patterns behind CVE-2026-16016

Casky has 331 skills that investigate the attack patterns behind CVE-2026-16016. Run one and get CVSS-scored findings in 3 minutes.

Run the skill that detects this →

X Instagram LinkedIn