Most static findings are false positives from Markdown fences, inline backticks, static Python imports, placeholders, and reference links. Confirmed risks are limited to low-severity dotenv and authenticated Microsoft Graph examples, with a medium semantic concern around broad OAuth .default scope usage. No prompt-injection attempt or malicious data-exfiltration intent was found.
Broad OAuth Default Scope in Copilot Studio Example
The Copilot Studio token request uses the Power Platform .default scope, which can request all pre-consented permissions for that resource. Production guidance should narrow or explicitly justify scopes.
The exact .default scope is present in the token request, and broad default scopes are a known permission-governance risk. The surrounding code is legitimate, so severity is medium rather than high.
The Graph profile example retrieves signed-in user data and sends the display name back into the conversation. This may expose profile data in chat transcripts if copied without data-minimization review.
The sample directly obtains a user token, calls the Graph profile endpoint, and sends displayName to chat. It is expected behavior but still creates a privacy review requirement.
Capability review items (4)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
The surrounding OAuth example uses aiohttp to make an authenticated Microsoft Graph request with a user bearer token. This is expected for the skill, but it is security-sensitive network and token handling.
The example sends a user OAuth bearer token to Microsoft Graph and retrieves profile data. The endpoint is legitimate, but copied implementations need consent, scope, and data-minimization controls.
The sample calls load_dotenv(), which can import local .env secrets into the process. This is common configuration practice, but it requires strict source-control and secret-management discipline.
The actual dotenv loader call reads local environment configuration. It is legitimate for Microsoft app credentials but still handles sensitive values.
Most static findings are false positives from Markdown fences, inline backticks, static Python imports, placeholders, and reference links. Confirmed risks are limited to low-severity dotenv and authenticated Microsoft Graph examples, with a medium semantic concern around broad OAuth .default scope usage. No prompt-injection attempt or malicious data-exfiltration intent was found.
Broad OAuth Default Scope in Copilot Studio Example
The Copilot Studio token request uses the Power Platform .default scope, which can request all pre-consented permissions for that resource. Production guidance should narrow or explicitly justify scopes.
The exact .default scope is present in the token request, and broad default scopes are a known permission-governance risk. The surrounding code is legitimate, so severity is medium rather than high.
The Graph profile example retrieves signed-in user data and sends the display name back into the conversation. This may expose profile data in chat transcripts if copied without data-minimization review.
The sample directly obtains a user token, calls the Graph profile endpoint, and sends displayName to chat. It is expected behavior but still creates a privacy review requirement.
Capability review items (4)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
The surrounding OAuth example uses aiohttp to make an authenticated Microsoft Graph request with a user bearer token. This is expected for the skill, but it is security-sensitive network and token handling.
The example sends a user OAuth bearer token to Microsoft Graph and retrieves profile data. The endpoint is legitimate, but copied implementations need consent, scope, and data-minimization controls.
The sample calls load_dotenv(), which can import local .env secrets into the process. This is common configuration practice, but it requires strict source-control and secret-management discipline.
The actual dotenv loader call reads local environment configuration. It is legitimate for Microsoft app credentials but still handles sensitive values.
Static findings mostly come from Markdown code fences, Python import examples, and documented setup commands rather than hidden executable skill behavior. The skill is legitimate Microsoft 365 agent guidance, but it has medium risk because examples load secrets from environment variables, acquire OAuth tokens, and make authenticated outbound calls to Microsoft services.
1
Files scanned
346
Lines analyzed
5
Review items
3
False positives ignored
Capability review items (2)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
The examples acquire tokens and send authenticated requests to Microsoft Graph, Azure OpenAI, and Copilot Studio endpoints. This is expected for the skill purpose, but misuse could expose user profile data or tenant resources if scopes and consent are not controlled.
The code clearly demonstrates token acquisition and authenticated network calls. The endpoints are Microsoft services and match the skill purpose, so this is a legitimate but sensitive pattern.
The skill instructs users to place client secrets, tenant IDs, Azure OpenAI endpoints, and API keys in environment configuration and load them at runtime. This is a standard pattern, but secrets must be protected and never committed.
The environment variable names include client secrets and API keys, and load_dotenv is used. The documentation also tells users to keep secrets out of source code, reducing malicious concern.
Static false positives ignored (3)
These static matches were dismissed by semantic review or matched schema-only tokens, so they are shown for transparency but do not drive the quality score.
Static import and Markdown execution false positives
The dynamic import and Ruby backtick findings are scanner artifacts from Python import blocks, Markdown inline code, and fenced examples. No evidence found that the skill itself executes hidden commands or dynamically imports untrusted code.
The referenced lines are Markdown formatting or ordinary Python imports and best-practice text. They do not show shell backtick execution, eval, or dynamic loading from user input.
The path traversal and hidden file warnings do not correspond to path traversal logic in the skill content. The flagged context is documentation and API scope text, not filesystem reads or writes.
The reviewed lines contain a newline in a status message and a Microsoft Power Platform scope ending in .default. No file path construction or traversal sink is present.
The reviewed skill content does not contain instructions that claim to override system policy, skip security analysis, or impersonate higher-priority instructions.
The file was reviewed for suspicious instruction language. No prompt injection attempt was found in the visible skill content.
This is a prompt-only instructional skill that provides code examples for building Microsoft 365 agents. Static analysis detected no security issues. The skill contains legitimate SDK usage patterns for aiohttp hosting, MSAL authentication, and Copilot Studio integration. Environment variable usage follows security best practices.