SkillTotal

Is Im Not Ai safe?

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

What to do: Nothing here argues against installing it. Grant the capabilities it lists only if you expect the tool to need them.

Im Not Ai is an AI component analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators. It can: filesystem read, filesystem write and shell execution — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).

repo

ai_component · https://github.com/epoko77-ai/im-not-ai
LOW
0
/ 100 risk score
Snapshot · scanned Oct 8, 2026 · repo@2f3d943 · engine 0.56.4 / ruleset 62

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

Capabilities — what this component can do (not a risk score):
filesystem readfilesystem writeshell 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

Findings (3)

HIGHPython shell/command executionST-SHELL-PY

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

return subprocess.run(
            ["git", "rev-parse", "--short", "HEAD"],
            cwd=_ROOT,
            capture_output=True,
            text=True,
            timeout=10,
        ).stdout.strip()

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.

raw = open(path, encoding="utf-8").read()
with open(_TAXONOMY, encoding="utf-8") as f:
with open(_OUT, encoding="utf-8") as f:
with open(_TAXONOMY, encoding="utf-8") as f:
with open(_HEADER, encoding="utf-8") as f:
with open(_FOOTER, encoding="utf-8") as f:
with open(_OUT, encoding="utf-8") as f:
with open(_TAXONOMY, encoding="utf-8") as f:
with open(_LEXICON, encoding="utf-8") as f:
with open(argv[1], encoding="utf-8") as f:
with open(argv[2], encoding="utf-8") as f:
with open(argv[1], encoding="utf-8") as f:
with open(args.inp, encoding="utf-8") as f, open(args.out, "w", encoding="utf-8") as out:
fixtures = json.loads(FIXTURES_PATH.read_text(encoding="utf-8"))["fixtures"]
return json.loads(p.read_text(encoding="utf-8"))
text = input_path.read_text(encoding="utf-8")
diagnosis = diag_path.read_text(encoding="utf-8")
manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
text = source_path.read_text(encoding="utf-8")
rewritten = (run_dir / c["rewritten_file"]).read_text(encoding="utf-8")
with open(args.before, encoding="utf-8") as f:
with open(args.after, encoding="utf-8") as f:
src = open(a.path, encoding="utf-8").read() if a.path else sys.stdin.read()
with open(args.before, encoding="utf-8") as f:
with open(args.after, 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(args.out, "w", encoding="utf-8") as f:
with open(_OUT, "w", encoding="utf-8") as f:
with open(_OUT, "w", encoding="utf-8") as f:
with open(args.inp, encoding="utf-8") as f, open(args.out, "w", encoding="utf-8") as out:
out_path.write_text(json.dumps(snapshot, ensure_ascii=False, indent=2), encoding="utf-8")
input_path.write_text(cleaned, encoding="utf-8")
(run_dir / "00_sanitize.json").write_text(
            json.dumps(report.to_dict(), ensure_ascii=False, indent=2),
            encoding="utf-8",
        )
input_path.write_text(args.text, encoding="utf-8")
error_path.write_text(
                    "metrics module import failed; chunk emitted without score block",
                    encoding="utf-8",
                )
metrics_path.write_text(
                        json.dumps(metrics_obj, ensure_ascii=False, indent=2),
                        encoding="utf-8",
                    )
error_path.write_text(
                        f"metrics_failed: {type(exc).__name__}: {exc}\n\n"
                        + traceback.format_exc(),
                        encoding="utf-8",
                    )
(run_dir / entry["input_file"]).write_text(combined, encoding="utf-8")
manifest_path.write_text(
        json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8"
    )
input_path.write_text(args.text, encoding="utf-8")
error_path.write_text(
            "metrics module import failed; combined file emitted without score block",
            encoding="utf-8",
        )
metrics_path.write_text(
                json.dumps(metrics_obj, ensure_ascii=False, indent=2),
                encoding="utf-8",
            )
error_path.write_text(
                f"metrics_failed: {type(exc).__name__}: {exc}\n\n"
                + traceback.format_exc(),
                encoding="utf-8",
            )
combined_path.write_text(
        _render_combined(text, metrics_obj, diagnosis=diagnosis), encoding="utf-8"
    )
output_path.write_text(out, encoding="utf-8")
(run_dir / args.report).write_text(
        json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8"
    )
with open(args.out, "w", encoding="utf-8") as f:
open(a.path, "w", encoding="utf-8").write(out)
with open(args.out, "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:

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.

How attackers abuse these capabilities

Interactive labs on the attack class behind the rules above. They show the technique, not anything found in Im Not Ai.

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