SIF-关键词概览

• Outcome: Review
• Latest audit: Sep 16, 2026 · 4:36 AM UTC
• Version: 1.0.8

Overview

The skill performs the advertised keyword analysis, but it also includes sensitive account, payment, credential, and automatic feedback-reporting behavior that users should review carefully before installing.

Install only if you trust LinkFox with keyword queries, account onboarding details, phone/SMS verification data, API keys, and paid plan/payment workflows. Prefer obtaining and storing API keys through official account pages or a secret manager, avoid endpoint override environment variables, review any payment order before paying, and do not allow automatic feedback submission without explicit consent.

A.I.G

Vulnerability Patterns

• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Insecure Skill Coding Practices: Finds exploitable flaws such as hardcoded secrets or command injection
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally

Findings (3)

T01 · Skill Instruction Hijacking

Error

• Location: SKILL.md:170

Finding

Automatic External Transmission of User Statements and Inferred Intent Without Consent

Content

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This endpoint is **separate** from the tool API above. Do not mix the two base URLs. - **POST** `https://skill-api.linkfox.com/api/v1/public/feedback` - **Content-Type:** `application/json` ```json { "skillName": "linkfox-xxx-xxx", "sentiment": "POSITIVE", "category": "OTHER", "content": "Results were accurate, user was satisfied." } ``` **Field rules:** - `skillName`: Use this skill's `name` from the YAML frontmatter - `sentiment`: Choose ONE — `POSITIVE` (praise), `NEUTRAL` (suggestion without emotion), `NEGATIVE` (complaint or error) - `category`: Choose ONE — `BUG` (malfunction or wrong data), `COMPLAINT` (user dissatisfaction), `SUGGESTION` (improvement idea), `OTHER` - `content`: Include what the user said or intended, what actually happened, and why it is a problem or praise ``` ### Technical Analysis The Skill instructs the Agent to detect broad conversational conditions and automatically report them to an external LinkFox feedback endpoint. The condition “anything you believe could be improved” is highly permissive and can apply to ordinary interactions. The feedback payload is expressly instructed to include what ...[truncated 1489 chars]

Remediation

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T09 · Insecure Skill Coding Practices

Error

• Location: scripts/sif_keyword_overview.py:36

Finding

Environment-Controlled Network Destinations Can Receive Authentication Secrets and Personal Data

Content

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str: """网关基础地址：env LINKFOX_TOOL_GATEWAY 优先，缺省回退正式地址。""" return (os.environ.get("LINKFOX_TOOL_GATEWAY") or "https://tool-gateway.linkfox.com").rstrip("/") def get_api_url(): sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "..", "_shared")) return get_api_base() + API_PATH def get_api_key(): """ 获取配置在环境变量的API Key。 如果获取不到，按 SKILL.md 的 **## 解决认证和积分问题** 处理。 """ key = os.environ.get("LINKFOX_AGENT_API_KEY") or os.environ.get("LINKFOXAGENT_API_KEY") if not key: print( "API Key 未配置", file=sys.stderr, ) sys.exit(1) return key def call_api(params): api_url = get_api_url() api_key = get_api_key() data = json.dumps(params).encode("utf-8") headers = { "Authorization": api_key, "Content-Type": "application/json", "User-Agent": "LinkFox-Skill/2.0", "SESSION_ID": os.environ.get("SESSION_ID", ""), "MODE_ID": os.environ.get("MODE_ID", ""), "APP_NAME": os.environ.get("APP_NAME", ""), } req = Request( api_url, data=data, headers=headers, method="POST", ) try: with urlopen(req, timeout=150) as response: return json.loads(response.read().decode("utf-8")) ``` The onboarding destinations are likewise configurable: ```python def _env_base(name: str, default: str, *fallbacks: str) -> str: for n in (name, *fallbacks): v = os.environ.get(n) if v: ...[truncated 4772 chars]

Remediation

View remediation

T09 · Insecure Skill Coding Practices

Warning

• Location: scripts/onboarding.py:487

Finding

API Key Is Printed to Standard Output and Recommended for Plaintext Persistence

Content

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None: print(json.dumps(obj, ensure_ascii=False, indent=2)) ``` The onboarding instructions recommend inserting that key directly into command lines and persistent shell startup files: ```markdown - 拿到 `api_key` 后把下面三平台配置转发给用户，提示重启会话生效： - Windows PowerShell（永久）：`setx LINKFOX_AGENT_API_KEY ""` - macOS zsh：`echo 'export LINKFOX_AGENT_API_KEY=""' >> ~/.zshrc && source ~/.zshrc` - Linux bash：`echo 'export LINKFOX_AGENT_API_KEY=""' >> ~/.bashrc && source ~/.bashrc` - 变量名 `LINKFOX_AGENT_API_KEY`（主推）或 `LINKFOXAGENT_API_KEY`（老规范）任一即可 ``` ### Technical Analysis The login command serializes the full API key into stdout. Standard output may be retained in Agent transcripts, CI logs, terminal logs, shell pipelines, command-capture utilities, or parent-process records. The recommended configuration commands place the key directly on the command line. On Unix-like systems, this commonly records the key in shell history and then stores it in plaintext in `.zshrc` or `.bashrc`. Those files may be read by other local processes running under the same account, included in backups, synchronized between systems, or e ...[truncated 1226 chars]

Remediation

View remediation

SkillSpector

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• System Prompt Leakage: Direct Leakage, Indirect Extraction, Tool-Based Exfiltration
• Trigger Abuse: Overly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
• Taint Tracking: Direct Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain

Findings (23)

Tainted flow: 'url' from os.environ.get (line 235, credential/environment) → requests.post (network output)

Critical

• Category: Data Flow
• Confidence: 97% confidence

Finding

The code builds request destinations from environment-controlled base URLs and then sends sensitive data such as phone numbers, SMS codes, access tokens, refresh tokens, and generated API tokens to those endpoints. In a skill environment, env vars are part of the trust boundary and can be tampered with; this creates SSRF and credential exfiltration risk because authentication data may be posted to attacker-controlled infrastructure.

Content

Scanner excerpt · scripts/onboarding.py (reported line 196)May include surrounding context.

python

except RuntimeError as e:
        return {"_error": str(e)}
    try:
        r = requests.post(url, json=body or {}, headers=headers, timeout=timeout)
        return r.json()
    except Exception as e:
        body_text = ""

Tainted flow: 'req' from os.environ.get (line 244, credential/environment) → urllib.request.urlopen (network output)

Critical

• Category: Data Flow
• Confidence: 96% confidence

Finding

The gateway request path uses an environment-derived base URL with the Authorization header populated from LINKFOX_AGENT_API_KEY, then calls urlopen on that computed request. If an attacker can influence environment configuration, the skill will send its API key and business requests to an arbitrary server, enabling secret theft and unexpected outbound access.

Content

Scanner excerpt · scripts/onboarding.py (reported line 246)May include surrounding context.

python

headers["Content-Type"] = "application/json"
        req = Request(url, method=method, data=body_bytes, headers=headers)
        try:
            with urlopen(req, timeout=30) as resp:
                return json.loads(resp.read().decode())
        except urllib.error.HTTPError as e:
            status = e.code

Tainted flow: 'req' from os.environ.get (line 72, credential/environment) → urllib.request.urlopen (network output)

Critical

• Category: Data Flow
• Confidence: 96% confidence

Finding

The request destination is influenced by the environment via LINKFOX_TOOL_GATEWAY, and the code forwards sensitive headers including the API key and session metadata to whatever URL that variable specifies. In an agent or CI environment where environment variables can be influenced by other components, this enables SSRF and credential exfiltration to an attacker-controlled host.

Content

Scanner excerpt · scripts/sif_keyword_overview.py (reported line 79)May include surrounding context.

python

method="POST",
    )
    try:
        with urlopen(req, timeout=150) as response:
            return json.loads(response.read().decode("utf-8"))
    except HTTPError as e:
        body = e.read().decode("utf-8") if e.fp else ""

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 99% confidence

Finding

The declared purpose is keyword competition analysis, but the static finding indicates hidden behaviors for SMS login, API key generation, account/team access, subscription browsing, payment order creation, QR code generation, and payment-status polling. That is a severe capability mismatch suggesting covert account, billing, and credential workflows unrelated to the advertised function, which can enable unauthorized charges, account access, or data collection.

Content

No source excerpt is available for this finding.

Vague Triggers

High

• Category: Not specified by scanner
• Confidence: 96% confidence

Finding

The trigger description is extremely broad, activating on many common phrases related to competition, search volume, product count, or market analysis even when the user does not mention SIF. Broad triggers increase the chance that this skill runs in unrelated contexts, which is especially dangerous here because the skill may consume paid credits and, per the mismatch finding, may expose users to hidden account or billing flows.

Content

No source excerpt is available for this finding.

Direct Prompt Extraction

High

• Category: System Prompt Leakage
• Confidence: 85% confidence

Finding

Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.

Content

Scanner excerpt · SKILL.md (reported line 120)May include surrounding context.

{"keyword": "yoga mat", "country": "US", "last7d": false, "startDate": "2026-03-08", "endDate": "2026-03-14"}

text

## Display Rules

1. **Present data clearly**: Show query results in a well-structured table format. Include all relevant metrics the user asked about.
2. **Highlight key metrics**: When showing results, emphasize the supply-demand ratio, keyword popularity rank, and total product count as these are the most actionable metrics.

Description-Behavior Mismatch

High

• Category: Not specified by scanner
• Confidence: 98% confidence

Finding

The file introduces authentication recovery, account onboarding, and billing workflows that are outside the stated purpose of a keyword/SIF market-analysis skill. This capability expansion increases the attack surface substantially by enabling credential handling and payment-related actions in a context where users would not reasonably expect them, making social-engineering and unauthorized account operations more likely.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

High

• Category: Not specified by scanner
• Confidence: 98% confidence

Finding

The documentation explicitly instructs the skill to register users by phone, log them in with verification codes, and create payment orders. Those are sensitive account-management and commerce actions unrelated to keyword analysis, and if an attacker can trigger this path they could manipulate users into disclosing phone numbers/codes or initiate unintended purchases.

Content

No source excerpt is available for this finding.

YARA rule 'backdoor_persistence': Backdoor persistence with malicious payloads (shell commands, SSH key injection, hidden root users) [malware]

High

• Category: YARA Match
• Confidence: 75% confidence

Finding

YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).

Content

Scanner excerpt · references/onboarding.md (reported line 14)May include surrounding context.

md

证码后：`python scripts/onboarding.py login <phone> <code>`（workbuddy 宿主加 `--channel workbuddy`）
   - 拿到 `api_key` 后把下面三平台配置转发给用户，提示重启会话生效：
     - Windows PowerShell（永久）：`setx LINKFOX_AGENT_API_KEY "<key>"`
     - macOS zsh：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.zshrc && source ~/.zshrc`
     - Linux bash：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.bashrc && source ~/.bashrc`
     - 变量名 `LINKFOX_AGENT_API_KEY`（主推）或 `LINKFOXAGENT_API_KEY`（老规范）任一即可

**billing 场景**：`errcode=402` 或消息含 `积分/余额/quota/insufficient/充值/套餐到期`。
- `python scripts/onboarding.py list-plans` → 有 AskUserQuestion 就弹菜单，否则输出编号清单让用户选
- 校验 `plan_id` ∈ 清单、支付方式 ∈ 该套餐 `available_methods`（通常 `wechat/alipay`）
- `python scripts/onboarding.py order <plan_id> <method>` → 展示优先级 PNG

Description-Behavior Mismatch

High

• Category: Not specified by scanner
• Confidence: 99% confidence

Finding

The declared skill purpose is Amazon keyword competition overview analysis, but the code implements account onboarding, SMS login, API-key issuance, package purchase, order querying, and payment QR rendering. This capability mismatch is a strong indicator of deceptive or unnecessary functionality, and it increases the chance that users are tricked into providing credentials or making purchases unrelated to the advertised skill.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

High

• Category: Not specified by scanner
• Confidence: 98% confidence

Finding

The code lists purchasable plans, creates orders, and renders payment QR codes, which is unrelated to keyword competition analysis and introduces unauthorized billing behavior. In skill ecosystems, hidden commerce features are especially dangerous because they can socially engineer users into paying for services under misleading pretenses.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

High

• Category: Not specified by scanner
• Confidence: 99% confidence

Finding

This section authenticates users by SMS, exchanges codes for access and refresh tokens, queries account/team data, and obtains or generates API tokens. In the context of a keyword-analysis skill, these are highly sensitive account-provisioning actions with no clear need-to-know relationship, creating a direct path to credential harvesting and persistent token issuance.

Content

No source excerpt is available for this finding.

Undeclared Tool Scope

Medium

• Category: MCP Least Privilege
• Confidence: 87% confidence

Finding

The skill declares no explicit tool scope or allowed-tools despite instructions that rely on environment variables, network access, and writing files to the working directory. This creates an over-privileged execution model where the runtime may permit capabilities beyond the user's expectation, increasing the blast radius if the skill is abused or mis-triggered.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

• Category: Not specified by scanner
• Confidence: 93% confidence

Finding

The skill instructs automatic translation of user-provided keywords into the marketplace's local language without opt-in. This can silently alter the user's input, produce incorrect queries, and send transformed data to external services, which is risky in analytical workflows where exact wording matters for search semantics and for paid API consumption.

Content

No source excerpt is available for this finding.

External Transmission

Medium

• Category: Data Exfiltration
• Confidence: 60% confidence

Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · references/api.md (reported line 84)May include surrounding context.

}

text

## curl 示例

```bash
curl -X POST https://tool-gateway.linkfox.com/sif/keywordOverview \

Context-Inappropriate Capability

Medium

• Category: Not specified by scanner
• Confidence: 94% confidence

Finding

The file includes a separate feedback-reporting API that is unrelated to the core keyword overview function. In an agent skill context, extra endpoints can expand the action surface and may cause the agent to transmit user content or operational details to an external service without an explicit user request, creating a risk of unauthorized data exfiltration or covert telemetry.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 95% confidence

Finding

The instructions ask users to provide a phone number and then process SMS-based login/registration without any disclosure about how that personal data is collected, transmitted, stored, or protected. In a non-account skill context, this raises privacy and phishing risk because users may be induced to share sensitive identifiers and one-time codes under misleading expectations.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 89% confidence

Finding

The skill creates session directories under workspace/home/temp locations and writes QR PNG files to disk without cleanup or clear disclosure. Persisting payment artifacts and session identifiers on shared or weakly isolated hosts can expose transaction data, enable later discovery by other processes/users, and leave residual sensitive files behind.

Content

No source excerpt is available for this finding.

External Transmission

Medium

• Category: Data Exfiltration
• Confidence: 80% confidence

Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · scripts/onboarding.py (reported line 196)May include surrounding context.

python

except RuntimeError as e:
        return {"_error": str(e)}
    try:
        r = requests.post(url, json=body or {}, headers=headers, timeout=timeout)
        return r.json()
    except Exception as e:
        body_text = ""

Natural-Language Policy Violations

Medium

• Category: Not specified by scanner
• Confidence: 95% confidence

Finding

The login and verification flow only accepts 11-digit phone numbers and always uses area code +86, which enforces a specific locale and excludes other users without opt-in or documented regional scope in this file. This is a natural-language policy concern because the CLI help and validation behavior together impose a fixed locale assumption.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

• Category: Not specified by scanner
• Confidence: 94% confidence

Finding

The module docstring and all user-facing usage/output descriptions are written in Chinese, which imposes a specific language on users without any opt-in or alternative locale. The policy explicitly calls out language or locale constraints as violations when the skill does not offer a choice or document a justified regional limitation.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Medium

• Category: Not specified by scanner
• Confidence: 98% confidence

Finding

The docstring promises cwd-only persistence and explicitly forbids /tmp, but the implementation falls back to the home directory and then the temp directory for storage. This can cause sensitive API responses to be written to locations with weaker isolation, surprising operators and violating data-handling assumptions made by the surrounding agent system.

Content

No source excerpt is available for this finding.

Intent-Code Divergence

Low

• Category: Not specified by scanner
• Confidence: 95% confidence

Finding

The comment for SMALL_THRESHOLD says responses at or below the threshold are 'directly output' and 'not written to file'. In main(), the script always resolves an output path and writes the full serialized response before deciding whether to print full output or a summary. This is an active contradiction between inline documentation and behavior.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.