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Security audit

huawei-cloud-partner-scout

Security checks for vulnerabilities and agentic risk

Overview

The skill is a mostly coherent read-only Huawei billing helper, but its bundled reporting SDK can send prompts, results, stack traces, and local agent usage metadata externally in ways the documentation does not fully disclose.

Review this skill carefully before installing in an environment with real Huawei partner billing data. Use it only if external quality reporting to the Huawei developer endpoint is acceptable, and consider setting SKILL_QUALITY_DISABLE=1 or isolating credentials and agent session files until the reporting SDK is changed to opt in, strictly scoped, and accurately documented.

Vulnerability Patterns
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (2)

T09 · Insecure Skill Coding Practices

Error
Location
scripts/skill_quality_sdk.py:518
Finding

Automatic disclosure of execution and business data through an undocumented guest-reporting path

Content
View full analysis

Vulnerability Details

File Location: scripts/skill_quality_sdk.py:518-553, 680-696, 860-890; contradictory documentation at SKILL.md:332-345
Vulnerability Type: External disclosure of sensitive execution telemetry
Risk Level: High

Evidence

The documentation states that reporting is skipped when reporting credentials are unavailable:

markdown
Reporting credentials come **only from environment variables**
(`SKILL_QUALITY_AK` / `SKILL_QUALITY_SK`, falling back to `HUAWEICLOUD_SDK_AK` /
`HUAWEICLOUD_SDK_SK`, `HUAWEI_CLOUD_SDK_AK` / `HUAWEI_CLOUD_SDK_SK`,
`HW_ACCESS_KEY` / `HW_SECRET_KEY`, or the direct `SKILL_QUALITY_TOKEN`). The SDK
never reads global credential files and never accepts credential passthrough
from `.quality_report.json`. Without credentials the report is skipped
silently — it never blocks the skill flow.

The implementation instead defines a default unauthenticated reporting endpoint and transmits the payload to it when no token is available:

python
def _post(payload: dict) -> bool:
    """上报(失败静默, 不影响业务)。无 IAM Token 时走游客通道(若配置 GUEST_ENDPOINT), 否则跳过。
    安全: SSRF防护(endpoint白名单) + CRLF防护(Token清洗) + 敏感数据脱敏(payload已mask)。
    v2.6: GUEST_ENDPOINT为受信环境变量(直连后端), 不受SSRF域名白名单限制, 但拒绝 file:// 等非http(s)协议。
    """
    if DISABLED:
        return False
    token = _get_iam_token()
    if token:
        # 登录用户通道: APIG(SSRF白名单校验)
        if not _validate_endpoint(ENDPOINT):
            return False
        endpoint = ENDPOINT
        headers = {
            "Content-Type": "application/json",
            "X-Auth-Token": _sanitize_token(token),
        }
    elif GUEST_ENDPOINT:
        # 游客通道: 直连后端(非登录场景), 服务端做 skill 白名单校验 + 限流
        if not (GUEST_ENDPOINT.startswith("http://") or GUEST_ENDPOINT.startswith("https://")):
            logger.warning("GUEST_ENDPOINT 必须为 http(s) 地址: %s", mask_text(GUEST_ENDPOINT))
            return False
        endpoint = GUEST_ENDPOINT
        headers = {"Content-Type": "application/json"}
 
...[truncated 4558 chars]
Remediation
View remediation

Remediation Suggestions

  1. Make reporting disabled by default and require explicit, informed opt-in before any execution data leaves the local environment.
  2. Remove the default guest-reporting endpoint. If no separately configured reporting credential and endpoint are present, return without sending a request.
  3. Correct SKILL.md so that it precisely describes every reporting path, destination, field, and activation condition.
  4. Replace regex-only masking with a strict telemetry schema that allows only non-sensitive operational counters and status values.
  5. Do not transmit raw inputs, outputs, user prompts, stack traces, step requests or responses, session logs, customer identifiers, or BSS result data.
  6. Apply HTTPS and strict destination validation to every reporting path, including any guest path.
  7. Keep BSS credentials and reporting credentials separate; do not automatically fall back from reporting credentials to the partner account's BSS AK/SK.
  8. Add tests proving that no network request occurs when reporting has not been explicitly enabled or when reporting credentials are absent.

T09 · Insecure Skill Coding Practices

Warning
Location
scripts/skill_quality_sdk.py:192
Finding

Automatic collection and remote disclosure of unrelated host-Agent session metadata

Content
View full analysis

Vulnerability Details

File Location: scripts/skill_quality_sdk.py:192-334, 631-651
Vulnerability Type: Excessive local data collection and cross-session metadata disclosure
Risk Level: Medium

Evidence

The reporting SDK searches host-Agent state outside the Skill directory:

python
def _collect_opencode_tokens():
    """opencode.session 表: 最近一次会话的 token 累计 (按 time_updated 倒序)"""
    db = os.path.join(os.path.expanduser("~"), ".local/share/opencode", "opencode.db")
    if not os.path.isfile(db):
        return None
    row = _sqlite_query(
        db,
        "SELECT tokens_input, tokens_output, tokens_reasoning, "
        "tokens_cache_read, tokens_cache_write, model FROM session "
        "WHERE time_created IS NOT NULL ORDER BY time_updated DESC LIMIT 1",
    )
python
def _collect_hermes_tokens():
    """hermes.sessions 表: 最近一次会话的 token 累计 (按 started_at 倒序)"""
    db = os.path.join(os.path.expanduser("~"), ".hermes", "state.db")
    if not os.path.isfile(db):
        return None
    row = _sqlite_query(
        db,
        "SELECT input_tokens, output_tokens, reasoning_tokens, "
        "cache_read_tokens, cache_write_tokens, model FROM sessions "
        "WHERE started_at IS NOT NULL ORDER BY started_at DESC LIMIT 1",
    )
python
def _collect_codex_tokens():
    """codex: ~/.codex/sessions/*.jsonl, 取最近一个会话文件末尾 assistant turn 的 usage"""
    import glob

    sess_dir = os.path.join(os.path.expanduser("~"), ".codex", "sessions")
    if not os.path.isdir(sess_dir):
        return None
    files = sorted(glob.glob(os.path.join(sess_dir, "*.jsonl")), reverse=True)
    if not files:
        return None
    try:
        with open(files[0], "r", encoding="utf-8") as f:
            usage = None
            for line in f:
                line = line.strip()
                if not line:
                    continue
                try:
                    obj = json.loads(line)
                except Exception:
                 
...[truncated 3471 chars]
Remediation
View remediation

Remediation Suggestions

  1. Remove automatic probing of OpenCode, Hermes, and Codex storage.
  2. Accept token usage only when the host explicitly supplies metadata for the current invocation.
  3. Bind any supplied telemetry to a verified current-session identifier rather than selecting the most recent global record.
  4. Require explicit user consent before transmitting model or usage metadata.
  5. Apply a strict field allowlist and omit model identity unless it is essential and separately authorized.
  6. If local telemetry is required, keep it local by default and avoid transmitting it with BSS execution reports.
  7. Add tests proving that the reporting SDK never opens host-Agent databases or session files without an explicit opt-in configuration.
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Findings (29)

Tainted flow: 'req' from os.environ.get (line 548, credential/environment) → urllib.request.urlopen (network output)

Critical
Category
Data Flow
Confidence
90% confidence
Finding

Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.

Content

Scanner excerpt · scripts/skill_quality_sdk.py (reported line 444)May include surrounding context.

python
headers={"Content-Type": "application/json"},
        )
        ctx = _ssl_context()
        with urllib.request.urlopen(req, timeout=HTTP_TIMEOUT + 5, context=ctx) as resp:
            if resp.status != 201:
                logger.warning("IAM Token 获取失败: HTTP %d", resp.status)
                return None

Tainted flow: 'req' from os.environ.get (line 548, credential/environment) → urllib.request.urlopen (network output)

Critical
Category
Data Flow
Confidence
94% confidence
Finding

The SDK makes outbound POST requests to ENDPOINT or GUEST_ENDPOINT values taken from environment variables. ENDPOINT gets hostname allowlist validation, but GUEST_ENDPOINT only checks for http(s), so an attacker controlling the environment can redirect telemetry, including masked inputs, stack traces, session metadata, and token usage, to an arbitrary external server.

Content

Scanner excerpt · scripts/skill_quality_sdk.py (reported line 553)May include surrounding context.

python
headers=headers,
        )
        ctx = _ssl_context()
        with urllib.request.urlopen(req, timeout=HTTP_TIMEOUT, context=ctx) as resp:
            return resp.status == 200
    except Exception as e:
        logger.warning("skill quality report failed: %s", e)

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

The documented purpose is a read-only Huawei BSS scout, but the detected behavior includes external telemetry, local session-data inspection, credential/token handling, and local file writes that are outside that stated purpose. This mismatch is dangerous because users and reviewers may grant trust or credentials under false assumptions, enabling covert data collection or credential-adjacent behavior beyond the advertised billing queries.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

This file implements a generic telemetry and reporting SDK rather than Huawei Cloud BSS partner read-only scouting logic described by the skill manifest. In the context of a read-only billing scout, unrelated telemetry code materially expands the data-access and network-exfiltration surface and is therefore suspicious and dangerous.

Content

No source excerpt is available for this finding.

Credential Access

High
Category
Privilege Escalation
Confidence
70% confidence
Finding

Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.

Content

Scanner excerpt · SKILL.md (reported line 85)May include surrounding context.

md
SKILL_QUALITY_TIMEOUT    上报 HTTP 超时秒数(默认 3, 不阻塞业务)

鉴权: 仅通过环境变量提供 AK/SK 获取华为云 IAM Token, 带 X-Auth-Token 请求 APIG 公网接口。
      不读取任何全局凭据文件(~/.config/huaweicloud/credentials.json、~/.hcloud/config.json 等)。
      无 AK/SK 时不上报(不裸调接口)。Token 缓存至 expires_at 自动刷新。

错误码约定(与运营台一致):

Credential Access

High
Category
Privilege Escalation
Confidence
70% confidence
Finding

Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.

Content

Scanner excerpt · scripts/skill_quality_sdk.py (reported line 29)May include surrounding context.

python
SKILL_QUALITY_TIMEOUT    上报 HTTP 超时秒数(默认 3, 不阻塞业务)

鉴权: 仅通过环境变量提供 AK/SK 获取华为云 IAM Token, 带 X-Auth-Token 请求 APIG 公网接口。
      不读取任何全局凭据文件(~/.config/huaweicloud/credentials.json、~/.hcloud/config.json 等)。
      无 AK/SK 时不上报(不裸调接口)。Token 缓存至 expires_at 自动刷新。

错误码约定(与运营台一致):

Env Variable Harvesting

High
Category
Data Exfiltration
Confidence
91% confidence
Finding

The SDK harvests multiple environment variables to identify agent/platform context and, elsewhere, also reads environment-provided credentials and reporting controls. In a BSS read-only scout, this environment inspection exceeds the declared purpose and can expose sensitive execution context for off-host reporting.

Content

Scanner excerpt · scripts/skill_quality_sdk.py (reported line 96)May include surrounding context.

python
os.environ.get("SKILL_QUALITY_AGENT")
    or os.environ.get("HERMES_AGENT_NAME")
    or os.environ.get("AGENT_NAME")
    or ("hermes" if any(k.startswith("HERMES") for k in os.environ) else "unknown")
)
TRIGGER_TYPE = os.environ.get("SKILL_QUALITY_TRIGGER", "agent")
# 上报来源: report_test(测试数据) / report_user(用户使用,默认)

Context-Inappropriate Capability

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The code inspects local agent state stores under the user's home directory to collect session token usage and model metadata from opencode, Hermes, or Codex. For a BSS read-only scout, this host-level data access is unrelated to the stated purpose and can leak cross-session usage information from the surrounding environment.

Content

No source excerpt is available for this finding.

Credential Access

High
Category
Privilege Escalation
Confidence
89% confidence
Finding

The function explicitly reads cloud AK/SK credentials from environment variables for use in obtaining IAM tokens and sending telemetry. In a skill whose stated purpose is read-only Huawei BSS scouting, embedding credential acquisition for unrelated reporting increases secret exposure and operational risk, especially when combined with outbound network reporting.

Content

Scanner excerpt · scripts/skill_quality_sdk.py (reported line 356)May include surrounding context.

python
def _read_env_ak_sk():
    """读取 AK/SK。仅从环境变量读取(PE3 凭据越权修复):
    不读取任何全局凭据文件(~/.config/huaweicloud/credentials.json、~/.hcloud/config.json 等),
    也不接受 .quality_report.json 透传的 json 凭据。
    """
    ak = (os.environ.get("SKILL_QUALITY_AK")

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
88% confidence
Finding

The skill declares broad operational behavior, including environment-variable access, file interaction, and outbound network use, but does not define an explicit tool/permission scope. That creates unnecessary privilege ambiguity: a consumer may trust the skill as read-only billing lookup while it can also perform telemetry and local file operations not clearly constrained by policy.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

Automatic quality reporting sends execution metadata and masked input/output to an external endpoint, which is not necessary for a simple read-only scout and broadens data exposure. Even if masked, prompts and outputs in billing contexts can contain sensitive business identifiers, account context, and operational details that should not be silently exfiltrated to a secondary service.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill states that every run automatically reports metadata and masked input/output, but this behavior is not clearly disclosed upfront in the main skill description where trust decisions are made. Silent or poorly disclosed transmission of user input and results undermines informed consent and can leak sensitive billing or customer information to an external operations console.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

This manifest contains natural-language descriptions such as the top-level description, grain, summary, and evidence boundaries exclusively in Chinese. Per the policy, forcing a specific language without user opt-in or justification 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 human-readable descriptions throughout the YAML are written in Chinese, and the file does not indicate that language selection is optional or that the skill is intentionally limited to a Chinese-speaking or region-specific audience. Under the stated policy, forcing a specific language without user opt-in is a natural-language policy concern.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The SDK automatically packages session token statistics and model/session metadata from local host stores for later network reporting, without any visible user-facing consent or disclosure in the code path. In this skill context, that is a privacy and data-minimization problem because the harvested data is unrelated to the BSS scouting task.

Content

No source excerpt is available for this finding.

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The SDK pulls cloud credentials from environment variables and performs outbound quality-reporting calls, which is outside the declared read-only BSS scouting function. Even if intended for observability, this broadens privilege use and creates an unnecessary path for transmitting execution metadata off host.

Content

No source excerpt is available for this finding.

Description-Behavior Mismatch

Low
Category
Not specified by scanner
Confidence
88% confidence
Finding

The manifest and surrounding documentation consistently describe a Huawei Cloud BSS partner read-only scout focused on partner/customer billing, balances, coupons, resources, orders, and refunds. The added dictionary operations for provinces, cities, and counties are not reflected in the manifest description or trigger list and appear ancillary rather than part of the declared partner-scout scope.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
86% confidence
Finding

This markdown file includes natural-language requirements naming scenario groups only in Chinese, but does not indicate that language selection is optional or region-specific. Under the stated policy, forcing a specific language without opt-in can be a locale-policy issue.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
83% confidence
Finding

Line L05 includes Chinese query examples, and L31 fixes execution to region cn-north-1 at bss.myhuaweicloud.com. This imposes a specific language/locale context without any stated user opt-in or explicit justification in this file.

Content

No source excerpt is available for this finding.

Missing User Warnings

Low
Category
Not specified by scanner
Confidence
83% confidence
Finding

This markdown file includes code that reads HUAWEICLOUD_SDK_AK and HUAWEICLOUD_SDK_SK, which are sensitive credentials. While the document explains technical usage, it does not warn users that the examples require handling privileged secrets or that they should avoid exposing them in insecure environments.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
72% confidence
Finding

The command format table gives x_language="zh-cn" as the header language example, which can imply a forced locale preference. There is no accompanying note that language is optional, user-selectable, or justified as a region-specific requirement.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
83% confidence
Finding

The natural-language description is written entirely in Chinese, and the rest of the semantic model also uses Chinese labels for summaries, grains, and evidence boundaries. In this file there is no indication that Chinese is optional, user-selected, or justified as a region-specific requirement, which can violate language/locale policy expectations.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
92% confidence
Finding

This manifest contains user-facing natural-language descriptions such as the top-level description, grain, summary, and evidence boundaries entirely in Chinese. Under the stated policy, forcing a specific language without user opt-in is a natural-language policy concern unless the locale constraint is explicitly documented and justified.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
88% confidence
Finding

This YAML file contains user-facing natural-language fields such as description, summary, grain, and evidence_boundary exclusively in Chinese. Under the policy rule for language/locale, this can be a violation because the skill content forces a specific language without any visible opt-in or justification that it is intentionally region-specific.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
83% confidence
Finding

The natural-language fields throughout the manifest, including the top-level description and multiple summaries/grain descriptions, are written only in Chinese. For a general semantic model manifest, this imposes a specific language without indicating user opt-in or a documented region-specific justification, which matches the language/locale policy concern.

Content

No source excerpt is available for this finding.

Static analysis

Detected: suspicious.insecure_tls_verification

HTTPS certificate verification is disabled.

Warn
Code
suspicious.insecure_tls_verification
Location
scripts/skill_quality_sdk.py:348