Back to skill

Security audit

GitLab Agent Profile

Security checks for vulnerabilities and agentic risk

Overview

The profile updater fits its purpose, but a bundled legacy renderer can automatically download and run extra software with access to available GitLab credentials.

Review the legacy npm fallback before use: prefer a preinstalled renderer and remove automatic package fetching. Verify the separately supplied production plugin before enabling scheduled publishing. Restrict GitLab access to intended projects, confirm the destination repository, and review generated assets. Public output intentionally includes aggregated private activity. This review found no artifact-backed basis for a malicious verdict.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Output HandlingUnvalidated Output Injection, Cross-Context Output, Unbounded Output
  • Behavioral ASTexec() Call, eval() Call, Dynamic Import
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Findings (11)

Skill declares no tool scope ('permissions' or 'allowed-tools') but code capabilities were detected: env, file_read, file_write, network, shell.

Medium
Category
MCP Least Privilege
Confidence
70% confidence
Finding

Without declared permissions the skill's intent is opaque and cannot be validated.

Content

No source excerpt is available for this finding.

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 25)May include surrounding context.

python
def glab_json(path: str) -> object:
    try:
        result = subprocess.run(
            ["glab", "api", path],
            check=True,
            text=True,

Tainted flow: 'path' from os.environ.get (line 191, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
65% confidence
Finding

Data from a source is assigned to a variable that is later passed to a sink, creating a variable-mediated taint flow.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 25)May include surrounding context.

python
def glab_json(path: str) -> object:
    try:
        result = subprocess.run(
            ["glab", "api", path],
            check=True,
            text=True,

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 40)May include surrounding context.

python
def current_user() -> str:
    result = subprocess.run(
        [
            "glab",
            "api",

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 384)May include surrounding context.

python
webp_output.parent.mkdir(parents=True, exist_ok=True)
    magick = shutil.which("magick")
    if magick:
        subprocess.run([magick, str(svg_output), str(webp_output)], check=True)
        return
    convert = shutil.which("convert")
    if convert:

Tainted flow: 'svg_output' from os.environ.get (line 457, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
65% confidence
Finding

Data from a source is assigned to a variable that is later passed to a sink, creating a variable-mediated taint flow.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 384)May include surrounding context.

python
webp_output.parent.mkdir(parents=True, exist_ok=True)
    magick = shutil.which("magick")
    if magick:
        subprocess.run([magick, str(svg_output), str(webp_output)], check=True)
        return
    convert = shutil.which("convert")
    if convert:

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 388)May include surrounding context.

python
return
    convert = shutil.which("convert")
    if convert:
        subprocess.run([convert, str(svg_output), str(webp_output)], check=True)
        return
    npm = shutil.which("npm")
    if npm:

Tainted flow: 'svg_output' from os.environ.get (line 457, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
65% confidence
Finding

Data from a source is assigned to a variable that is later passed to a sink, creating a variable-mediated taint flow.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 388)May include surrounding context.

python
return
    convert = shutil.which("convert")
    if convert:
        subprocess.run([convert, str(svg_output), str(webp_output)], check=True)
        return
    npm = shutil.which("npm")
    if npm:

The WebP fallback can download and execute an npm package without disclosing that behavior.

Medium
Category
Output Handling
Confidence
98% confidence
Finding

The fallback silently permits downloading and executing an unpinned sharp-cli package through npm exec --yes rather than requiring an existing renderer. This creates a supply-chain execution path with the script's filesystem access and inherited authentication environment; being a legacy reference lowers exposure, but not the potential consequence if run.

Content

No source excerpt is available for this finding.

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
97% confidence
Finding

Unlike the other subprocess calls, this fallback invokes npm exec --yes with an unpinned package, allowing npm to fetch and execute code when a suitable local package is unavailable. Compromised package code or installation scripts could access inherited credentials and workspace files; the documented legacy-only status reduces normal exposure but does not make direct invocation safe.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 392)May include surrounding context.

python
return
    npm = shutil.which("npm")
    if npm:
        subprocess.run(
            [
                npm,
                "exec",

Tainted flow: 'svg_output' from os.environ.get (line 457, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
65% confidence
Finding

Data from a source is assigned to a variable that is later passed to a sink, creating a variable-mediated taint flow.

Content

Scanner excerpt · scripts/update-profile-stats.py (reported line 392)May include surrounding context.

python
return
    npm = shutil.which("npm")
    if npm:
        subprocess.run(
            [
                npm,
                "exec",