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Security audit

每日新闻搜索与智能摘要

Security checks for vulnerabilities and agentic risk

Overview

This is a real Chinese news digest skill, but it needs review because it can reuse an OpenClaw API key and make broad network requests without clear user opt-in.

Install only if you are comfortable with a local news scraper that writes a SQLite database and desktop/workspace digest files. Before running the full pipeline, remove the OpenClaw config fallback or set dedicated, limited NEWS_DIGEST_LLM credentials, validate the LLM endpoint, and avoid using untrusted custom source databases or arbitrary article links.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
Findings (5)

T05 · Unauthorized Access and Privilege Escalation

Error
Location
scripts/news_digest_v2/stage2_5_llm_summary.py:26
Finding

Silent Access and Use of an Unrelated OpenClaw API Credential

Content
View full analysis

Vulnerability Details

File Location: scripts/news_digest_v2/stage2_5_llm_summary.py, lines 26–75
Vulnerability Type: Unauthorized credential access and use
Risk Level: High

Vulnerable Code

python
# LLM Configuration (use environment variables, fallback to OpenClaw config)
API_KEY = os.environ.get('NEWS_DIGEST_LLM_API_KEY', '')
BASE_URL = os.environ.get('NEWS_DIGEST_LLM_BASE_URL', '')
MODEL = os.environ.get('NEWS_DIGEST_LLM_MODEL', 'qwen3.6-plus')

def load_llm_config():
    """Fallback: try to load from OpenClaw config if env vars not set"""
    global API_KEY, BASE_URL
    if API_KEY and BASE_URL:
        return True
    try:
        config_path = os.path.expanduser(r"~\.openclaw\openclaw.json")
        with open(config_path, 'r', encoding='utf-8-sig') as f:
            config = json.load(f)
        provider = config['models']['providers']['custom-coding-dashscope-aliyuncs-com']
        API_KEY = provider['apiKey']
        BASE_URL = provider['baseUrl']
        return True
    except Exception as e:
        print(f"  ⚠️ LLM config load failed: {e}")
        return False

def call_llm(prompt, max_tokens=4000, temperature=0.3):
    """Call LLM API"""
    if not API_KEY or not BASE_URL:
        load_llm_config()
    if not API_KEY or not BASE_URL:
        print(f"  ⚠️ LLM not configured, skipping summary")
        return None
    if not API_KEY:
        return None

    req_data = json.dumps({
        'model': MODEL,
        'messages': [{'role': 'user', 'content': prompt}],
        'temperature': temperature,
        'max_tokens': max_tokens
    }).encode('utf-8')

    req = urllib.request.Request(
        f'{BASE_URL}/chat/completions',
        data=req_data,
        headers={
            'Authorization': f'Bearer {API_KEY}',
            'Content-Type': 'application/json'
        }
    )

    try:
        with urllib.request.urlopen(req, 
...[truncated 2609 chars]
Remediation
View remediation

Remediation Suggestions

  • Remove the OpenClaw configuration fallback entirely.
  • Require explicit NEWS_DIGEST_LLM_API_KEY and NEWS_DIGEST_LLM_BASE_URL values dedicated to this Skill.
  • Keep LLM processing disabled unless the user explicitly opts in.
  • Update the full workflow so Stage 2.5 is called only when explicit LLM configuration and consent are present.
  • Validate the LLM endpoint:
    • Require HTTPS.
    • Permit only expected hostnames and ports.
    • Reject embedded credentials, fragments, loopback addresses, private addresses, link-local addresses, and redirects to unapproved hosts.
  • Clearly disclose that article titles, sources, and up to 800 characters of article content per item are transmitted.
  • Use a narrowly scoped API key with usage limits and separate billing controls.
  • Never print credentials or include authorization headers in exception details.

T09 · Insecure Skill Coding Practices

Error
Location
scripts/news_digest_v2/config.py:17
Finding

Server-Side Request Forgery Through Database-Configured Sources and Extracted Article Links

Content
View full analysis

Vulnerability Details

File Location: scripts/news_digest_v2/config.py, lines 17–42; scripts/news_digest_v2/fetcher.py, lines 278–325, 627–695, and 843–916
Vulnerability Type: Unrestricted outbound request and SSRF
Risk Level: High

Vulnerable Code

The source URLs are loaded directly from SQLite:

python
def load_websites():
    """Load monitored websites from the database, sorted by priority."""
    try:
        conn = sqlite3.connect(DB_PATH)
        cursor = conn.cursor()
        cursor.execute('''
            SELECT id, name, url, selector, category, priority
            FROM monitor_websites
            WHERE enabled = 1
            ORDER BY priority, category, id
        ''')
        websites = []
        for row in cursor.fetchall():
            websites.append({
                'id': row[0],
                'name': row[1],
                'url': row[2],
                'selector': row[3],
                'category': row[4],
                'priority': row[5] if len(row) > 5 else 3
            })
        conn.close()
        return websites
    except Exception as e:
        print(f"Failed to load website configuration: {e}")
        return get_default_websites()

Requests are made without destination validation:

python
response = requests.get(
    url,
    headers=current_headers,
    timeout=actual_timeout,
    verify=verify_ssl
)
response.raise_for_status()
return decode_response(response, url)

Extracted absolute links are accepted without enforcing the source hostname:

python
for a in soup.find_all('a', href=True):
    url = a['href']
    title = a.get_text(strip=True)

    if not title or len(title) < 5:
        continue

    if url.startswith('//'):
        url = 'https:' + url
    elif not url.startswith('http'):
        url = urljoin(base_url, url)
        if not url.startswith('http'):
   
...[truncated 3323 chars]
Remediation
View remediation

Remediation Suggestions

  • Require HTTPS for all source and article URLs.
  • Maintain an explicit allowlist of approved source hostnames and permitted ports.
  • Restrict discovered article links to the configured source hostname or a narrowly defined set of related domains.
  • Resolve every destination before connecting and reject:
    • Loopback addresses.
    • Private IPv4 and IPv6 ranges.
    • Link-local addresses.
    • Multicast, reserved, unspecified, and documentation ranges.
    • Cloud metadata destinations.
  • Disable automatic redirects or validate every redirect target using the same policy.
  • Protect against DNS rebinding by connecting only to the validated resolved address and rechecking each new connection.
  • Parse URLs with urllib.parse.urlsplit() rather than relying on string prefixes.
  • Reject embedded credentials, unexpected ports, malformed hostnames, and non-HTTP schemes.
  • Treat the configured SQLite database as security-sensitive and restrict its filesystem permissions.
  • Do not forward fetched content to an LLM unless its source has passed destination and provenance validation.

T09 · Insecure Skill Coding Practices

Warning
Location
scripts/news_digest_v2/fetcher.py:298
Finding

TLS Certificate Verification Is Disabled for Government Sites and Certificate Errors

Content
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Vulnerability Details

File Location: scripts/news_digest_v2/fetcher.py, lines 298–325
Vulnerability Type: Improper certificate validation
Risk Level: Medium

Vulnerable Code

python
# Special handling for gov.cn
is_gov = 'www.gov.cn' in url
current_headers = HEADERS.copy()
if is_gov:
    current_headers['User-Agent'] = (
        'Mozilla/5.0 (Windows NT 10.0; Win64; x64) '
        'AppleWebKit/537.36 (KHTML, like Gecko) '
        'Chrome/114.0.0.0 Safari/537.36'
    )
    current_headers['Accept'] = (
        'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8'
    )
    current_headers['Accept-Encoding'] = 'gzip, deflate'
    verify_ssl = False
else:
    verify_ssl = True

response = requests.get(
    url,
    headers=current_headers,
    timeout=actual_timeout,
    verify=verify_ssl
)
response.raise_for_status()
return decode_response(response, url)

except requests.exceptions.SSLError:
    try:
        response = requests.get(
            url,
            headers=HEADERS,
            timeout=timeout,
            verify=False
        )
        response.raise_for_status()
        return decode_response(response, url)
    except Exception as e2:
        _flog(f"Fetch failed during SSL fallback: {url} - {e2}")
        return None

Related warning suppression occurs in scripts/news_digest_v2/fetcher.py, lines 11–15:

python
import urllib3
import warnings

warnings.filterwarnings(
    "ignore",
    category=urllib3.exceptions.InsecureRequestWarning
)

Technical Analysis

URLs containing www.gov.cn are fetched without certificate verification from the outset. For every other HTTPS destination, any certificate validation failure triggers a second request with verify=False.

Certificate validation is the mechanism that authenticates the remote server and protects HTTPS traffic against interception. Retr ...[truncated 1573 chars]

Remediation
View remediation

Remediation Suggestions

  • Remove every use of verify=False.
  • Fail closed when certificate validation fails.
  • Use the operating system trust store or a maintained CA bundle.
  • If a particular server requires an additional CA, configure that CA specifically rather than disabling verification.
  • Remove suppression of InsecureRequestWarning and avoid blanket warning suppression in the full pipeline.
  • Parse and compare normalized hostnames rather than searching for domain substrings.
  • Require HTTPS and apply the same strict verification policy to all redirects.
  • Add tests proving that expired, self-signed, hostname-mismatched, and untrusted certificates are rejected.

T01 · Skill Instruction Hijacking

Warning
Location
scripts/news_digest_v2/stage2_5_llm_summary.py:89
Finding

Indirect Prompt Injection Through Untrusted Scraped Article Content

Content
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Vulnerability Details

File Location: scripts/news_digest_v2/stage2_5_llm_summary.py, lines 89–132
Vulnerability Type: Indirect prompt injection
Risk Level: Medium

Vulnerable Code

python
def llm_summarize_batch(batch_news_list, batch_num, batch_total):
    """Summarize one batch"""
    articles_text = ""
    for i, n in enumerate(batch_news_list):
        content_snippet = (
            n.get('content', '') or n.get('summary', '')
        )[:800]

        raw_title = n['title']
        has_cyrillic = bool(re.search(r'[а-яА-Я]', raw_title))
        if has_cyrillic:
            articles_text += (
                f"[{i+1}] {n['source']}:"
                f"(abnormal title encoding; generate a title from the body)\n"
                f"{content_snippet}\n\n"
            )
        else:
            articles_text += (
                f"[{i+1}] {n['source']}:{n['title']}\n"
                f"{content_snippet}\n\n"
            )

    prompt = f"""You are a professional news editor. Summarize each of
    the following {len(batch_news_list)} news articles.

    Requirements:
    1. Preserve core facts.
    2. Do not merely repeat the title.
    3. Use concise professional language.
    4. Include the full name of referenced policy documents.
    5. Keep each summary within the configured length.
    6. Remove datelines and reporter bylines.
    7. Use the requested numbered format.
    8. Regenerate titles marked as incorrectly encoded.
    9. Apply the specified title-rewriting rules.
    10. Do not invent information.

    News list:
    {articles_text}

    Begin:"""

    response = call_llm(
        prompt,
        max_tokens=4000,
        temperature=0.3
    )

Technical Analysis

Titles and article bodies obtained from external websites are inserted directly into the same user-role message that contains the summarization instructions. The ...[truncated 1980 chars]

Remediation
View remediation

Remediation Suggestions

  • Treat every title, source, and article body as untrusted data.
  • Place behavioral rules in the highest-priority message supported by the API.
  • Explicitly instruct the model that article text may contain malicious commands and that no instruction inside an article may be followed.
  • Submit articles as structured JSON fields rather than concatenated prose.
  • Use clear per-article boundaries and length limits.
  • Request a strict JSON response conforming to a defined schema.
  • Validate that every returned item maps to an input article and that no extra fields or records are present.
  • Reject summaries containing instruction-like output, unexpected markup, external calls to action, or content unsupported by the source.
  • Consider an extractive or non-agentic summarization method for untrusted sources.
  • Preserve the original title and summary so suspicious LLM output can be compared and discarded.

T08 · Insecure Dependencies

Note
Location
SKILL.md:14
Finding

Unpinned Runtime Dependency Installation

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, lines 14–18 and 219–222
Vulnerability Type: Unsafe dependency and package-source guidance
Risk Level: Low

Vulnerable Code

bash
# Step 1: Install dependencies
pip install requests beautifulsoup4

The troubleshooting instructions also suggest an alternate package index:

bash
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple requests beautifulsoup4

Technical Analysis

The installation commands do not constrain package versions and do not verify package hashes. As a result, installation behavior can change over time as new package releases are published.

The alternate index instruction changes the supply-chain trust boundary without providing version pins or integrity checks. The listed package names are legitimate and no typosquatting or malicious package was identified, but the installation procedure does not provide reproducibility or protection against a future compromised release or package mirror.

Attack Path

  1. A user follows the documented setup instructions.
  2. pip resolves the latest package versions available from the selected index.
  3. A compromised package release, account, index, or mirror serves malicious or altered package content.
  4. Package installation or later import executes the supplied code with the user's privileges.

This path depends on compromise of a dependency distribution channel; no such compromise was observed in the audited project.

Impact Assessment

A compromised dependency can execute with the privileges of the user running pip or the news-digest scripts. That can expose local files, credentials, network access, and project data.

The current project does not intentionally request elevated installation privileges, so the maximum practical scope depends on whether the user independently runs the installation as an administrator.

Remediation
View remediation

Remediation Suggestions

  • Provide a reviewed requirements.txt or lockfile with exact versions.
  • Include SHA-256 hashes and install with pip --require-hashes.
  • Document the supported Python version and periodically update pinned packages after security review.
  • Prefer the official Python Package Index unless an organization has explicitly approved and secured another mirror.
  • If alternate mirrors are documented, retain hash verification so package integrity does not depend solely on the mirror.
  • Recommend installation in a dedicated virtual environment without administrator privileges.
  • Add automated dependency vulnerability and provenance scanning to the release process.
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Tool MisuseTool Parameter Abuse, Chaining Abuse, Unsafe Defaults
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
Findings (49)

Tainted flow: 'req' from os.environ.get (line 65, credential/environment) → urllib.request.urlopen (network output)

Critical
Category
Data Flow
Confidence
90% confidence
Finding

The code sends prompts to a network endpoint whose base URL is taken from environment variables or a user-scoped config file, with no allowlist or validation. That means a modified environment or local config can redirect article contents and the bearer token to an attacker-controlled server, causing credential exfiltration and unauthorized disclosure of scraped news data.

Content

Scanner excerpt · scripts/news_digest_v2/stage2_5_llm_summary.py (reported line 75)May include surrounding context.

python
)

    try:
        with urllib.request.urlopen(req, timeout=300) as resp:
            result = json.loads(resp.read().decode('utf-8'))
            return result.get('choices', [{}])[0].get('message', {}).get('content', '')
    except Exception as e:

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

The description claims an end-to-end news digest skill: scraping Chinese news, processing content, and generating formatted daily summaries. However, this code chunk is explicitly labeled as 'stage 2' and only performs two backend operations: duplicate detection in a database and keyword tagging for recent records. These are supporting processing tasks, but the chunk lacks the core declared behaviors of scraping/fetching news and producing digest outputs with sources and links. Because the actual code's primary purpose is a narrower internal pipeline step rather than the declared user-facing news digest capability, this is a material description-behavior mismatch.

Content

No source excerpt is available for this finding.

Ae1

High
Category
analysis-evasion
Confidence
100% confidence
Finding

Referenced artifact was not completely inspected

Content

Scanner excerpt · SKILL.md (reported line 281)May include surrounding context.

md
- `fetcher.py` 新增 `decode_response()` 函数,对已知 GBK 编码来源(人民日报海外版)强制使用 GBK 解码,从根源修复 Cyrillic 乱码

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
91% confidence
Finding

The skill documentation describes capabilities that access environment variables, read and write local files, and perform network scraping, but it declares no explicit tool scope or permissions boundary. This creates an authorization ambiguity where an agent may invoke broader capabilities than a user expects, increasing the risk of unintended filesystem writes, secret exposure from environment variables, or uncontrolled outbound requests.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

The manifest description and title position the skill specifically around Chinese news sources and Chinese-language digest usage, including Chinese trigger phrases, but do not indicate that users can choose another language or locale. Under the policy rule, a skill that imposes a specific language/locale should either offer opt-in or clearly document a justified regional constraint.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
89% confidence
Finding

The documentation states that execution writes output both to a workspace file and to a Desktop text file, but it does not prominently warn users about these filesystem side effects or provide a safer default location. Writing to Desktop is especially risky in agent contexts because it can leak sensitive content into user-visible locations, overwrite files, or violate execution-environment expectations.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
89% confidence
Finding

The module docstring states that the skill scrapes web content and saves it to a database, which expands behavior beyond a simple output-generation news digest. Hidden or under-declared data storage increases risk because operators and users may not expect persistence of scraped content, retention obligations, or downstream use of stored data.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The Accept-Language header is fixed to "zh-CN,zh;q=0.9,en;q=0.8", which imposes a specific language/locale preference at runtime. Under the policy, forcing a locale without user opt-in or a clearly justified region-specific constraint is a natural-language policy violation.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The module docstring and all operational descriptions are written entirely in Chinese, which indicates a language-specific skill behavior and documentation without any stated user choice or locale justification. Under the policy, forcing a specific language without opt-in is a natural-language policy concern.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

This code file contains natural-language text in Chinese in the module docstring, function docstrings, comments, and at least one printed status message. Under the stated policy, forcing a specific language without user opt-in is a locale/language policy violation unless the constraint is explicitly documented and justified, which is not present here.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The documentation says this function marks '最近一次抓取的新数据' (data from the most recent scrape), which implies scrape-batch semantics. The actual code does not track scrape runs and instead sets new_flag for every article whose created_at is within the last hour, which can include rows from multiple runs or miss an older latest run.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
87% confidence
Finding

The module's docstrings, comments, logs, and user-visible print messages are written entirely in Chinese, and there is no indication that language is configurable or that the skill is intentionally limited to a Chinese-only audience. Under the stated policy, forcing a specific language without user opt-in can be a locale-policy violation.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

The fetcher intentionally disables TLS certificate verification for gov.cn requests, allowing a man-in-the-middle attacker to spoof the remote site and feed arbitrary content into the pipeline. In a scraping-and-summarization skill, that can poison downstream summaries, contaminate stored data, and mislead users with attacker-controlled news content presented as trusted government material.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
98% confidence
Finding

The code disables SSL verification both proactively for one domain and again in the SSL-exception fallback, without any user-facing notice or hard failure. That permits silent acceptance of spoofed HTTPS endpoints, which is especially dangerous here because the skill ingests untrusted remote content and may store or summarize it as if it were authentic news.

Content

No source excerpt is available for this finding.

Unsafe Defaults

Medium
Category
Tool Misuse
Confidence
99% confidence
Finding

Setting verify_ssl = False for gov.cn hardcodes insecure transport as the default behavior for that source. Because this skill's purpose is to collect and present credible news, accepting unverifiable HTTPS materially increases the risk of misinformation, poisoned summaries, and persistence of attacker-supplied content.

Content

Scanner excerpt · scripts/news_digest_v2/fetcher.py (reported line 311)May include surrounding context.

python
current_headers['Accept'] = 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8'
            current_headers['Accept-Encoding'] = 'gzip, deflate'
            # gov.cn 可能存在 SSL 策略,尝试不验证
            verify_ssl = False 
        else:
            verify_ssl = True

Unsafe Defaults

Medium
Category
Tool Misuse
Confidence
99% confidence
Finding

Using verify=False in the SSL fallback creates an unsafe default where certificate failures are silently converted into trusted content fetches. An attacker controlling network traffic can exploit this to inject arbitrary HTML that the system may parse, summarize, log, and persist, undermining the integrity of the digest output.

Content

Scanner excerpt · scripts/news_digest_v2/fetcher.py (reported line 321)May include surrounding context.

python
except requests.exceptions.SSLError:
        # SSL 错误时尝试不验证证书
        try:
            response = requests.get(url, headers=HEADERS, timeout=timeout, verify=False)
            response.raise_for_status()
            return decode_response(response, url)
        except Exception as e2:

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
92% confidence
Finding

When USE_LLM_SUMMARY is enabled, the code sends full article content and title to llm_summarize_article, which is a network/data-transmission operation if backed by an external model service. The file contains no user-facing disclosure that fetched content may be transmitted to an LLM provider for summarization.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The manifest emphasizes producing formatted summaries with source attribution and original links. Here the code appends each item with a content field containing the full scraped article text, which expands the skill's actual data collection behavior beyond the stated digest-generation role.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
85% confidence
Finding

The manifest describes scraping, processing, and generating daily news digests with formatted summaries and links. In addition to that, this file persists the collected news corpus via save_to_database(all_news), which is a separate storage behavior not mentioned in the skill description.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
89% confidence
Finding

This file contains natural-language instructions and documentation exclusively in Chinese, including the module docstring and inline comments. That can violate language/locale policy when a skill forces a specific language without user opt-in or justification, and no such opt-in or justification is present in this file.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
88% confidence
Finding

The module docstrings and generated user-facing output strings are written in Chinese only, with no indication that the user can choose a language or locale. This creates a language policy issue because the skill imposes a specific language in its natural-language behavior without offering opt-in or configuration.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium
Category
Not specified by scanner
Confidence
89% confidence
Finding

The manifest describes a skill for scraping, processing, and generating formatted news digests, but this file also persists the generated content to specific local filesystem targets including the user's Desktop. Saving artifacts to local files is a materially broader behavior than in-memory formatting and is not stated in the manifest description.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

This code performs file writes to multiple destinations, including the user's Desktop and Feishu-related output files, but there is no confirmation prompt, print/log disclosure, or inline warning to the user at the point of action. For a formatter module, silently persisting generated content to local files can affect user data and should be clearly disclosed.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

Producing a daily digest does not inherently require writing files to a user-specific Desktop path derived from environment data. This introduces host-side file persistence behavior that is separate from scraping and summarization and is not called out in the manifest's stated scope.

Content

No source excerpt is available for this finding.

Tainted flow: 'out_file' from os.environ.get (line 172, credential/environment) → open (file write)

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/news_digest_v2/formatter.py (reported line 173)May include surrounding context.

python
desktop = os.path.join(os.environ.get('USERPROFILE', ''), 'Desktop')
            today_str = datetime.now().strftime('%Y%m%d_%H%M%S')
            out_file = os.path.join(desktop, f"新闻摘要_{today_str}.txt")
            with open(out_file, 'w', encoding='utf-8') as f:
                f.write(output_text)
            saved_to.append(out_file)

Static analysis

Detected: suspicious.insecure_tls_verification

HTTPS certificate verification is disabled.

Warn
Code
suspicious.insecure_tls_verification
Location
scripts/news_digest_v2/fetcher.py:321