SkillTotal

Is Agentic Seo Skill safe?

No malicious indicators - review capabilities before installing
Notable — review in context (capabilities are not malware):
  • Python shell/command execution
  • Python network egress
  • Python filesystem read

agentic-seo-skill is an AI python_package analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators, though 5 risky constructs are reported for review. It can: delegated authentication, filesystem read, filesystem write, network egress and shell execution — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).

agentic-seo-skill 3.0.1

python_package · https://github.com/Bhanunamikaze/Agentic-SEO-Skill
LOW
0
/ 100 risk score
Snapshot · scanned Aug 5, 2026 · agentic-seo-skill@3.0.1 · engine 0.38.1 / ruleset 42

Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of Agentic Seo Skill's authors. Report a false positive.

Capabilities — what this component can do (not a risk score):
delegated authenticationfilesystem readfilesystem writenetwork egressshell execution

Behavioral traits

How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.

Execution authority
Tool Access Control / Direct Tool Access
Filesystem reach
Tool Execution Context
Network egress
Interaction & Communication / Direct Communication
Delegated authentication
Tool Execution Context / User Delegated Credentials

Findings (5)

HIGHPython shell/command executionST-SHELL-PY

The component can run operating-system commands or spawn processes.

result = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
result = subprocess.run(
            ["gh", "--version"],
            stdout=subprocess.DEVNULL,
            stderr=subprocess.DEVNULL,
            check=False,
            text=True,
        )
result = subprocess.run(
            ["gh", "auth", "status", "-h", "github.com"],
            capture_output=True,
            text=True,
            check=False,
            timeout=12,
        )
output = subprocess.check_output(
            ["git", "remote", "get-url", "origin"],
            cwd=cwd,
            stderr=subprocess.DEVNULL,
            text=True,
        ).strip()
result = subprocess.run(
            cmd,
            input=input_data,
            capture_output=True,
            text=True,
            timeout=timeout,
            check=False,
        )
result = subprocess.run(cmd, capture_output=True, text=True, check=False)
completed = subprocess.run(args, check=False, capture_output=True, text=True, timeout=timeout)
output = subprocess.check_output(
            ["git", "for-each-ref", "--sort=-creatordate", "--format=%(refname:short)%09%(creatordate:iso8601)", f"--count={limit}", "refs/tags"],
            cwd=cwd,
            stderr=subprocess.DEVNULL, …

Why it matters: Powerful and often legitimate — confirm the commands aren't built from untrusted input.

Fix: Confirm the command and its arguments are fully controlled and not derived from untrusted input; avoid shell=True.

MEDIUMPython filesystem readST-FS-PY-READ

The component reads files from disk.

with open(source, "r", encoding="utf-8") as fh:
return path.read_text(encoding="utf-8"), "", {"url": source, "status": None, "headers": {}, "error": None}
with open(source, "r", encoding="utf-8") as fh:
with open(path, newline="", encoding="utf-8-sig") as fh:
with open(source, "r", encoding="utf-8") as fh:
return path.read_text(encoding="utf-8"), "", {"url": source, "status": None, "headers": {}, "error": None}
with open(source, "r", encoding="utf-8") as fh:
text = path.read_text(encoding="utf-8")
with open(path, "r", encoding="utf-8") as fh:
with open(args.findings_json, "r", encoding="utf-8") as f:
with open(args.context_json, "r", encoding="utf-8") as f:
return path.read_text(encoding="utf-8"), "", {"url": source, "status": None, "headers": {}, "error": None}
with open(source, "r", encoding="utf-8") as fh:
with open(path, "r", encoding="utf-8") as f:
with open(html_path, "r", encoding="utf-8", errors="ignore") as f:
with open(args.query_file, "r", encoding="utf-8") as f:
with open(path, "r", encoding="utf-8") as f:
markdown = read_text(args.readme_path)
with open(args.query_file, "r", encoding="utf-8") as f:
with open(args.query_file, "r", encoding="utf-8") as f:
return path.read_text(encoding="utf-8"), "", {"url": source, "status": None, "headers": {}, "error": None}
return path.read_text(encoding="utf-8"), "", {"url": source, "status": None, "headers": {}, "error": None}
payload = json.loads(Path(path).read_text(encoding="utf-8"))
return open(path, "r", encoding="utf-8", errors="replace")
with open(real_path, "r", encoding="utf-8") as f:

Why it matters: Usually legitimate, but worth confirming it can't be steered into reading sensitive files.

Fix: Confirm which files are read and that paths cannot be influenced by untrusted input to reach sensitive locations.

MEDIUMPython filesystem write/deleteST-FS-PY-WRITE

The component writes or deletes files on disk.

with open(path, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(path, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(args.markdown, "w", encoding="utf-8") as f:
with open(args.action_plan, "w", encoding="utf-8") as f:
with open(args.output, "w", encoding="utf-8") as f:
with open(path, "a", encoding="utf-8") as f:
with open(path, "w", encoding="utf-8") as f:

Why it matters: Usually legitimate, but worth confirming the paths can't be controlled by untrusted input.

Fix: Confirm which files are written/deleted and that paths cannot be influenced by untrusted input.

MEDIUMPython network egressST-NET-PY

The component makes outbound network requests.

from urllib.parse import urlparse
from urllib.parse import urlparse
parsed = urlparse(normalize_url(url))
f"?client=chrome&q={urllib.parse.quote(query)}"
from urllib.parse import urlparse
domain = urlparse(url).netloc.replace(".", "_")
from urllib.parse import urljoin, urlparse
absolute = urljoin(base_url, href)
"is_internal": urlparse(absolute).netloc == urlparse(base_url).netloc,
from urllib.parse import urlparse
return urlparse(value).scheme in ("http", "https") or ("." in value and "/" not in value)
path = urlparse(url).path.lower()
from urllib.parse import urlparse
from urllib.parse import urlparse
page_host = urlparse(url).netloc if url else ""
host = urlparse(link.get("href", "")).netloc
from urllib.parse import parse_qs, urlparse
params = parse_qs(urlparse(url).query)
href_params = parse_qs(urlparse(tag.get("href")).query)
from urllib.parse import urlparse, urljoin
parsed = urlparse(site_url)

Why it matters: Usually legitimate, but confirm the destinations are expected and no sensitive data leaves.

Fix: Confirm the destination hosts are expected and that no sensitive data is sent off-host.

LOWDelegated authentication (OAuth 2.0 / OIDC)ST-AUTH-DELEGATED

An OAuth 2.0 / OpenID Connect delegated-authentication flow was detected (authorization-code / refresh-token / token-exchange grant, an OIDC authorize/discovery endpoint or id_token, or a delegation library). Tools authenticate with the end user's delegated, scoped credentials rather than a long-lived embedded service credential. (3 occurrence(s) shown as evidence).

pip install google-api-python-client google-auth-oauthlib
print("Error: google-api-python-client and google-auth-oauthlib required.", file=sys.stderr)
print("Install with: pip install google-api-python-client google-auth-oauthlib", file=sys.stderr)

Fix: Delegated auth is a lower-blast-radius execution context than an embedded static credential. Confirm the requested scopes are minimal and that tokens are never logged or forwarded off-host.

Check your own component

Run the same evidence-backed scan on any MCP server, agent skill, or package.

Scan your own component

How we determine this: deterministic static analysis (regex + AST), evidence-anchored, no code execution. Methodology →