T09 · Insecure Skill Coding Practices
- Location
skills/smyx_common/scripts/config.yaml:4- Finding
Private Surveillance Video and Authentication Data Can Be Transmitted over Plaintext HTTP
- Content
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- Remediation
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The skill is related to elder-monitoring video analysis, but it silently creates and reuses identities, stores service tokens, and is configured to send sensitive video and credentials over plaintext development HTTP endpoints.
Review this carefully before installing. It handles extremely sensitive in-home video and historical safety reports, creates or reuses an internal account identity automatically, and may store reusable service tokens locally. Do not use it for real household monitoring unless the publisher removes the dev HTTP configuration, uses HTTPS-only allowlisted endpoints, clearly documents account creation/token retention/deletion, and confirms consent, retention, and access-control practices.
skills/smyx_common/scripts/config.yaml:4Private Surveillance Video and Authentication Data Can Be Transmitted over Plaintext HTTP
skills/smyx_common/scripts/util.py:548Authentication Credentials Are Automatically Attached to Arbitrary Absolute URLs
skills/smyx_common/scripts/util.py:548Silent Remote Account Registration Persists Service Tokens in Unencrypted Database Fields
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
Automatic remote login/account creation, token handling, persistent open-id generation, workspace discovery, and file access are high-sensitivity operations that are not transparently disclosed by the stated purpose. In a skill processing in-home elder surveillance data, these hidden identity and storage behaviors substantially elevate privacy, consent, and unauthorized data correlation risks.
When no identity is provided, the code silently creates a synthetic default user in a local database and then reuses it. For a home-monitoring alert skill, this creates an undisclosed identity lifecycle and enables backend interactions under fabricated or implicit accounts, which can misattribute actions, weaken auditability, and expose user data to external services without informed consent.
The utility layer performs remote account login/registration, caches tokens, and persists user identity data even though the skill is described as elderly immobility video monitoring and alerting. That is a material capability expansion: the code can create or reuse identities and communicate with external health-related services without clear necessity or user consent, increasing the risk of unauthorized account actions and privacy leakage.
The manifest documents capabilities that involve shell execution, network access, file reads/writes, and environment use, but it does not declare any tool scope or permission boundaries. This creates a least-privilege failure: an agent may invoke powerful operations implicitly, making misuse, unintended data access, or command execution harder to govern and audit.
The documentation expands the input surface from continuous video monitoring to still images, arbitrary local files, and URLs. Broader input modalities increase the chance of unintended file access, ingestion of sensitive local content, or server-side fetching of untrusted remote resources that users may not expect from the declared camera-monitoring scenario.
An overly broad default trigger can cause the skill to activate on uploaded home-monitoring media whenever analysis is requested, even when the user did not intend elder-care processing. Because the skill may perform file handling, network/API calls, and identity-linked reporting, accidental invocation can expose sensitive household footage to unnecessary processing paths.
The skill exposes cloud-based historical report querying and listing beyond the primary activity-detection use case, but this secondary data-access interface is only partially disclosed. In a system handling elder-care reports, expanding into history retrieval increases the risk of over-collection, unintended disclosure, or access to past sensitive records.
Broad auto-trigger keywords for history-report retrieval can cause unintended access or display of prior sensitive reports without strong intent verification. In this context, accidental retrieval of elder-care history is a meaningful privacy risk because reports may be identity-linked and contain health-adjacent safety events.
The document describes continuous in-home camera monitoring across private spaces and emergency alerting, but provides no privacy notice, consent requirements, retention limits, access controls, or guidance for handling highly sensitive personal data. In the context of monitoring an elderly person inside a home, especially including bedroom and bathroom coverage, this omission can lead to invasive surveillance deployments, unauthorized disclosure, and non-compliant processing of sensitive data.
The hardcoded user-facing string on L17 is entirely in Chinese and provides no indication that language is configurable or selected based on user preference. This creates a natural-language policy concern because the skill appears to enforce a specific language/locale without opt-in or documented justification in this file.
The script resolves an internal user identity via OpenIdUtil.resolve_current_open_id() without meaningful user disclosure and even suppresses the related CLI option from help output. In a monitoring tool handling highly sensitive in-home elder video analysis and alert history, hidden identity binding can cause actions or data retrieval to occur under an unexpected account, creating privacy, authorization, and auditability risks.
Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
result_json = JsonUtil.parse(result_json_pure_text, result_json_pure_text)
result_json_common_ai_response = result_json.get("commonAiResponse") if isinstance(result_json,
dict) else result_json
if result_json_common_ai_response:
result_json = result_json_common_ai_response
Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
result_json = JsonUtil.parse(result_json_pure_text, result_json_pure_text)
result_json_common_ai_response = result_json.get("commonAiResponse") if isinstance(result_json,
dict) else result_json
if result_json_common_ai_response:
result_json = result_json_common_ai_response
The user-facing output headers and messages are hard-coded in Chinese, such as the report title and export-link text. Because this is a code file and there is no indication that the skill is region-specific or that users can opt into the locale, this appears to violate the language/locale policy for natural-language content.