SkillTotal

Is Gpt Image2 Ppt Skills 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

repo is an AI agent_skill analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators, though 4 risky constructs are reported for review. It can: 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).

repo

agent_skill · https://github.com/JuneYaooo/gpt-image2-ppt-skills
LOW
0
/ 100 risk score
Snapshot · scanned Aug 5, 2026 · repo@4576cd5 · 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 Gpt Image2 Ppt Skills's authors. Report a false positive.

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

Findings (4)

HIGHPython shell/command executionST-SHELL-PY

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

result = subprocess.run(
                argv,
                capture_output=True,
                text=True,
                timeout=self.timeout,
                check=False,
            )
result = subprocess.run(
            [path, *args],
            check=False,
            capture_output=True,
            text=True,
            timeout=timeout,
        )
result = subprocess.run(
            [sys.executable, "-m", "pip", "install", "pywin32"],
            check=False, capture_output=True, text=True,
        )
result = subprocess.run(
            ["osascript", "-e", script],
            check=True, capture_output=True, text=True, timeout=120,
        )
subprocess.run(
                [cli, "--headless", "--convert-to", "pdf",
                 "--outdir", str(out_pdf.parent), str(pptx_path)],
                check=True, capture_output=True, text=True,
            )

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.

return json.loads(path.read_text(encoding="utf-8")), path.parent
with open(image_path, "rb") as image_file, open(mask_path, "rb") as mask_file:
data = json.loads(scene_path.read_text(encoding="utf-8"))
with open(meta_path, "r", encoding="utf-8") as f:
with open(meta_path, "r", encoding="utf-8") as f:
with open(style_path, "r", encoding="utf-8") as f:
with open(sidecar, "r", encoding="utf-8") as f:
return json.loads(path.read_text(encoding="utf-8"))
with open(prompts_path, "r", encoding="utf-8") as f:
with open(prompt_path, "r", encoding="utf-8") as f:
with open(args.template_profile, "r", encoding="utf-8") as f:
with open(args.plan, "r", encoding="utf-8") as f:
with open(path, "rb") as f:
with open(ref_path, "rb") as f:
plan = md_to_plan(src.read_text(encoding="utf-8"))
with open(path, "rb") as f:
manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
with open(path, "rb") as f:
with open(pptx_path, "rb") as f:
with open(cache_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.

report_path.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
path.write_bytes(self._decode_first_image(response))
path.write_bytes(self._decode_first_image(response))
report_path.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
with open(prompts_path, "w", encoding="utf-8") as f:
_shutil.copy2(png, current)
_shutil.copy2(current_img, versioned_img)
with open(prompt_abs, "w", encoding="utf-8") as f:
_shutil.copy2(current_img, versioned_new)
_shutil.copy2(current_img, versioned_img)
with open(prompt_abs, "w", encoding="utf-8") as f:
_shutil.copy2(current_img, versioned_new)
with open(prompt_abs, "w", encoding="utf-8") as pf:
_shutil.copy2(image_path, versioned_initial)
with open(output_path, "wb") as f:
with open(output_path, "wb") as f:
dst.write_text(json.dumps(plan, ensure_ascii=False, indent=2), encoding="utf-8")
_render_manifest_path(out_dir).write_text(
        json.dumps(manifest, ensure_ascii=False, indent=2),
        encoding="utf-8",
    )
shutil.rmtree(dest_prefix, ignore_errors=True)
with open(cache_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
resp = requests.get(url, stream=True, timeout=REQUEST_TIMEOUT_SECS)
resp = requests.post(
            url, headers=headers, json=payload,
            stream=True, timeout=REQUEST_TIMEOUT_SECS,
        )
resp = requests.post(url, headers=headers, json=payload, timeout=REQUEST_TIMEOUT_SECS)
resp = requests.post(
                    self.endpoint, headers=headers, json=payload, timeout=VISION_TIMEOUT_SECS
                )

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.

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