Secure your dependencies. Ship with confidence.

The code exhibits multiple anomalies and potential security risks, including the use of unconventional methods, dynamic error handling, and potential obfuscation. Further investigation is required to determine the extent of the risks.

The Python module itself is not directly implementing typical malware behaviors, but it creates a high-risk execution surface: it runs local shell scripts (some with sudo) with unvalidated inputs and passes secrets on the command line. The deploy_fdb_from_file_service function contains a command-injection vulnerability (shell=True with joined args) and a coding bug (returncod typo). Recommend: remove shell=True; use argument lists always, avoid passing secrets via argv (use stdin, environment files with proper filesystem permissions, or secured IPC), eliminate unnecessary sudo calls and require callers to provide appropriate privileges if needed, validate/escape inputs (especially file paths), fix the returncod typo, and audit all invoked shell scripts before use. Treat package as risky until mitigations and script audits are performed.

While the Socket.IO/Engine.IO client portions appear functionally conventional, this module also embeds a Web Worker that dynamically imports Socket.IO from a CDN, connects to an external endpoint (with a suspicious hardcoded default IP), and periodically sends registration/heartbeat messages that include a caller-provided secret. It further implements a server-side kill-switch ('terminated_by_server') to disconnect the client. In a supply-chain context, this is a strong indicator of malicious or unauthorized telemetry/beaconing behavior unless the surrounding project explicitly documents and justifies this exact worker-based secret-bearing heartbeat functionality.

This test suite documents and exercises functionality that, in the implementation, would harvest Discord authentication tokens from local storage, macOS keychain, or by executing JS in Discord's renderer process via CDP. Those behaviors amount to credential theft and intrusive process manipulation (killing/relaunching apps to enable debug ports). Even though this file is tests/mocks, it strongly indicates the associated module is designed for malicious activity (token exfiltration). Use of such a module in production or client environments would present a high security risk and is not recommended.

This script is exfiltrating sensitive system information (hostname, current user, current directory) to a remote server without the user's consent. This behavior is highly suspicious and poses a significant security risk.

Live on npm for 26 minutes before removal. Socket users were protected even while the package was live.

This fragment is a targeted, destructive tool that enumerates Python processes and forcefully kills those matching hard-coded project/team patterns. It lacks input validation, ownership checks, graceful termination, auditing, and error handling. While not exfiltrating data or using obfuscation, its behavior constitutes sabotage/denial-of-service of local processes and is unsafe to run on shared systems or production hosts. Recommend not executing this code; if similar behavior is required for legitimate maintenance, reimplement with strict validation, user/UID checks, safer termination signals, confirmation/logging, and PID parsing safeguards.

This module contains explicit data-exfiltration behavior: ctx.send_message transmits caller-controlled strings to a hardcoded external endpoint on repl.co. The combination of an untrusted remote host, lack of validation/authentication, and a network call that could leak sensitive data makes this unsuitable for production or for inclusion without review. The broken 'command' function adds further concern about code quality or tampering. Recommend removing or replacing the remote endpoint, adding strict input validation and authentication, and fixing the broken helper; if this file appears unexpectedly in a dependency tree, treat the package as suspicious and investigate the publisher and integrity (checksums/signatures).

The setup.py itself is benign and not obfuscated, but it packages and exposes an entry point for a project that explicitly advertises itself as an initial access/post-exploitation tool for Azure AD/O365. That makes the overall package high risk. The provided fragment cannot prove active malicious operations, but the declared intent and the entrypoint that will execute undisclosed code at runtime justify treating the package as malicious/unsafe until a full audit of GraphSpy.* modules and bundled assets is performed.

This module contains a critical remote code execution primitive: it deserializes received message.callback using eval and then executes the resulting function, passing in the local foglet instance and emitter. Incoming data is sourced from network/peer messages, and the interpreter also supports remote method dispatch by message.name. Together, these enable attacker-controlled code execution and potential propagation across peers. Treat as extremely dangerous and do not use in untrusted or loosely authenticated peer environments.

The code engages in potentially malicious behavior by collecting sensitive system information and sending it to a remote server without clear user consent. The hard-coded domain, data obfuscation, and lack of transparency raise significant privacy and security concerns. The risk score is high due to the invasive nature of the code.

Live on npm for 18 minutes before removal. Socket users were protected even while the package was live.

This file automatically sends internal dumpJSON items to a third-party AI Studio endpoint (https://bbqa2t5pfyfroyobmzknmktshckzto4btkfagxyjqwy[.]did[.]abtnet[.]io/ai-studio/api/datasets/443696818363039744/documents) whenever the module is loaded. It embeds a hard-coded Cookie header—including a login_token JWT—and uses it to first fetch existing documents and then PUT or POST JSON-serialized item data under “text” paths. There is no user consent, opt-in, or error handling; the behavior runs as a side effect, leaks potentially sensitive package metadata, and abuses embedded credentials to write to an external service. This is a high-risk supply-chain/backdoor indicator.

This module implements a remote access agent that grants interactive shell control and arbitrary file-read capabilities to any remote party that knows the short numeric secret. Key issues: the encryption key is a low-entropy 6-digit number (guessable/brute-forceable), the relay URL is hard-coded, there is no authentication beyond the shared code, file reads are unrestricted, and environment variables are exposed to the spawned shell. These characteristics make the module high risk in general use and it can be abused for data exfiltration and remote command execution. If intended for legitimate remote support, additional protections are required: stronger key exchange, authenticated peers, allowlisting/sandboxing of filesystem access, logging/visibility, and operator confirmation before granting shell control.

[Skill Scanner] Pipe-to-shell or eval pattern detected All findings: [CRITICAL] command_injection: Pipe-to-shell or eval pattern detected (CI013) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] This skill/instruction doc appears functionally legitimate and aligned with its stated purpose (YouTube thumbnail design using a remote inference CLI). However, it contains moderately high supply-chain risk patterns: a curl|sh installer that downloads and executes a CLI from inference.sh/dist.inference.sh, plus examples that send prompts and (potentially) images and authentication tokens to a third-party service. There are no hardcoded secrets or obfuscated code in the provided text. Recommend treating the installer pattern as risky: prefer pinned, auditable installs (manual checksum verification before execution), clear documentation on where credentials go, and least-privilege CLI invocation. Overall: no clear malware, but medium-to-high supply-chain/security risk due to download-and-execute and credential/ data-forwarding patterns. LLM verification: The SKILL.md is a benign thumbnail-design guide but instructs users to install and use a third-party CLI via a pipe-to-shell pattern and to authenticate that CLI. The immediate risks are supply-chain and credential exposure: executing a remote install script and sending prompts/files/credentials to external inference endpoints. There is no embedded malware in the text itself, but the recommended operational flow is high-risk. Recommendation: do not execute the pipe-to-shell installer without ind

This module is an automation/scraping worker that intentionally executes code provided by task descriptions. That design requires trusting the task source. The code contains multiple high-risk sinks: subprocess with shell=True, exec()/eval of task-supplied code, and browser JS execution. It also copies browser user profiles (cookies/credentials) into temporary profiles, which increases risk of credential theft. If task inputs are untrusted (remote server controlled by attacker or tampered local JSON), an attacker can achieve remote code execution, data exfiltration (files, cookies), or arbitrary system changes. Recommendation: only run with tasks from trusted sources, disable remote task fetching unless secured, avoid copying full user-data profiles, and remove/guard exec/eval/subprocess paths or run worker inside a hardened sandbox/container with least privileges.

The module itself is not obviously obfuscated or pre-packed with a secret backdoor, but it enables high-risk behavior: downloading/unzipping arbitrary content and executing it with shell=True, and extracting zip files unsafely. If an attacker can control ExecuteConfig (particularly exe_url, exe_path, exe_unzip_and_use, or command_suffix) or the downloaded resource, they can achieve remote code execution and arbitrary filesystem changes. Recommend treating this module as dangerous in untrusted contexts: enforce strict input validation, verify integrity/signatures of downloads, avoid shell=True by passing args as a list, sanitize zip entries before extractall, and implement cleanup of temp files.

Live on pypi for 2 hours and 44 minutes before removal. Socket users were protected even while the package was live.

The SweetAlert2 library code is mostly benign and serves as a UI modal dialog tool. However, it contains a suspicious and potentially malicious snippet that targets Russian users on certain domains to play an unsolicited audio prank, disabling pointer events and potentially disrupting user interaction. This behavior is unexpected and should be considered a moderate security risk and potential malware. The rest of the code shows no signs of malicious intent. The provided reports were invalid and unhelpful. Users should be cautious about this version of the library due to the embedded prank behavior.

This module is a high-risk remote-control/backdoor component: it exposes unauthenticated remote command execution (shell, exec, eval), arbitrary file upload and download, and background task creation. It should be treated as malicious/untrusted in most deployment contexts. Do not run this code on production or internet-accessible hosts. Immediate remediation: remove or quarantine the component, revoke any credentials/keys on the host, perform forensic audit for persistence or additional compromise, and block network access to any running instance.

The code exposes powerful administrative actions: arbitrary shell execution, arbitrary file reads, full environment dumps, and building/pushing Docker images to a hardcoded registry. These are not obfuscated but are high-risk capabilities that can be abused for data exfiltration, remote code execution, and supply-chain leakage if the superuser authentication is compromised or misconfigured. The presence of a hardcoded remote image name for docker push is suspicious for unintended outbound artifact exfiltration. Recommendation: avoid including these endpoints in public packages or ensure strict, auditable authentication and input validation; remove hardcoded push targets and avoid returning full environment variables or arbitrary file contents.

High-confidence malicious active data exfiltration: the script enumerates and base64-encodes all files under /opt and posts them to a hardcoded external webhook. Treat as confirmed compromise. Remove the code, block the destination domain, investigate systems that executed the module, rotate any credentials that may have been exposed, and perform forensic collection of affected hosts.

The OpenClaw and multi-source Tech News Digest footprint present a coherent workflow for aggregating, deduplicating, scoring, enriching, and delivering digests via multiple formats. However, the reliance on numerous environment-stored credentials, optional backends, and a prompt-driven orchestration introduces multiple risk vectors for secret leakage, supply-chain drift, and prompt-injection-like control if templates or prompts are improperly audited. The design is plausible for legitimate use but exhibits medium-to-high supply-chain risk due to credential management complexity, lack of explicit secret rotation, and broad outbound data flows. Recommended improvements include: adopting a centralized secret store with rotation policies, enforcing TLS pinning and strict back-end authentication defaults, implementing per-backend access controls and key rotation, adding explicit data minimization and consent policies, enabling script integrity verification (signing, hashing, pinned dependencies), and auditing the prompt templates (digest-prompt.md) for prompt-injection risk. Overall security risk remains moderate to high until mitigations are in place; malware likelihood remains low given no signs of payload delivery, but misconfigurations could enable data leakage or abuse.

This file is part of a malicious package that exploits software distribution infrastructure for social engineering attacks. The assembly metadata contains extensive promotional content advertising illegal Snapchat account hacking services, including detailed descriptions of traffic-based attack methods against Snapchat servers. The file directs users to visit an external malicious website at hacksgames[.]online/Snap-Hack/ through embedded URLs in assembly descriptions. While containing no executable malicious code (only empty class implementations), it serves as a delivery mechanism to redirect users to potentially harmful external sites that could distribute malware, conduct phishing attacks, or engage in other malicious activities. This represents supply chain pollution by abusing legitimate package repositories to promote illegal services and poses significant security risks to users who may follow the embedded malicious links.

This snippet conditionally executes shell commands in CI based on an environment variable index. It includes an explicit fetch-and-execute command that pipes a remote script into bash without integrity checks. Combined with exec-based shell command execution and environment-driven command selection, this represents a high supply-chain/execution risk and should be reviewed/removed or replaced with integrity-verified, pinned, and non-piped remote code handling.

The code exhibits multiple anomalies and potential security risks, including the use of unconventional methods, dynamic error handling, and potential obfuscation. Further investigation is required to determine the extent of the risks.

The Python module itself is not directly implementing typical malware behaviors, but it creates a high-risk execution surface: it runs local shell scripts (some with sudo) with unvalidated inputs and passes secrets on the command line. The deploy_fdb_from_file_service function contains a command-injection vulnerability (shell=True with joined args) and a coding bug (returncod typo). Recommend: remove shell=True; use argument lists always, avoid passing secrets via argv (use stdin, environment files with proper filesystem permissions, or secured IPC), eliminate unnecessary sudo calls and require callers to provide appropriate privileges if needed, validate/escape inputs (especially file paths), fix the returncod typo, and audit all invoked shell scripts before use. Treat package as risky until mitigations and script audits are performed.

While the Socket.IO/Engine.IO client portions appear functionally conventional, this module also embeds a Web Worker that dynamically imports Socket.IO from a CDN, connects to an external endpoint (with a suspicious hardcoded default IP), and periodically sends registration/heartbeat messages that include a caller-provided secret. It further implements a server-side kill-switch ('terminated_by_server') to disconnect the client. In a supply-chain context, this is a strong indicator of malicious or unauthorized telemetry/beaconing behavior unless the surrounding project explicitly documents and justifies this exact worker-based secret-bearing heartbeat functionality.

This test suite documents and exercises functionality that, in the implementation, would harvest Discord authentication tokens from local storage, macOS keychain, or by executing JS in Discord's renderer process via CDP. Those behaviors amount to credential theft and intrusive process manipulation (killing/relaunching apps to enable debug ports). Even though this file is tests/mocks, it strongly indicates the associated module is designed for malicious activity (token exfiltration). Use of such a module in production or client environments would present a high security risk and is not recommended.

This script is exfiltrating sensitive system information (hostname, current user, current directory) to a remote server without the user's consent. This behavior is highly suspicious and poses a significant security risk.

Live on npm for 26 minutes before removal. Socket users were protected even while the package was live.

This fragment is a targeted, destructive tool that enumerates Python processes and forcefully kills those matching hard-coded project/team patterns. It lacks input validation, ownership checks, graceful termination, auditing, and error handling. While not exfiltrating data or using obfuscation, its behavior constitutes sabotage/denial-of-service of local processes and is unsafe to run on shared systems or production hosts. Recommend not executing this code; if similar behavior is required for legitimate maintenance, reimplement with strict validation, user/UID checks, safer termination signals, confirmation/logging, and PID parsing safeguards.

This module contains explicit data-exfiltration behavior: ctx.send_message transmits caller-controlled strings to a hardcoded external endpoint on repl.co. The combination of an untrusted remote host, lack of validation/authentication, and a network call that could leak sensitive data makes this unsuitable for production or for inclusion without review. The broken 'command' function adds further concern about code quality or tampering. Recommend removing or replacing the remote endpoint, adding strict input validation and authentication, and fixing the broken helper; if this file appears unexpectedly in a dependency tree, treat the package as suspicious and investigate the publisher and integrity (checksums/signatures).

The setup.py itself is benign and not obfuscated, but it packages and exposes an entry point for a project that explicitly advertises itself as an initial access/post-exploitation tool for Azure AD/O365. That makes the overall package high risk. The provided fragment cannot prove active malicious operations, but the declared intent and the entrypoint that will execute undisclosed code at runtime justify treating the package as malicious/unsafe until a full audit of GraphSpy.* modules and bundled assets is performed.

This module contains a critical remote code execution primitive: it deserializes received message.callback using eval and then executes the resulting function, passing in the local foglet instance and emitter. Incoming data is sourced from network/peer messages, and the interpreter also supports remote method dispatch by message.name. Together, these enable attacker-controlled code execution and potential propagation across peers. Treat as extremely dangerous and do not use in untrusted or loosely authenticated peer environments.

The code engages in potentially malicious behavior by collecting sensitive system information and sending it to a remote server without clear user consent. The hard-coded domain, data obfuscation, and lack of transparency raise significant privacy and security concerns. The risk score is high due to the invasive nature of the code.

Live on npm for 18 minutes before removal. Socket users were protected even while the package was live.

This file automatically sends internal dumpJSON items to a third-party AI Studio endpoint (https://bbqa2t5pfyfroyobmzknmktshckzto4btkfagxyjqwy[.]did[.]abtnet[.]io/ai-studio/api/datasets/443696818363039744/documents) whenever the module is loaded. It embeds a hard-coded Cookie header—including a login_token JWT—and uses it to first fetch existing documents and then PUT or POST JSON-serialized item data under “text” paths. There is no user consent, opt-in, or error handling; the behavior runs as a side effect, leaks potentially sensitive package metadata, and abuses embedded credentials to write to an external service. This is a high-risk supply-chain/backdoor indicator.

This module implements a remote access agent that grants interactive shell control and arbitrary file-read capabilities to any remote party that knows the short numeric secret. Key issues: the encryption key is a low-entropy 6-digit number (guessable/brute-forceable), the relay URL is hard-coded, there is no authentication beyond the shared code, file reads are unrestricted, and environment variables are exposed to the spawned shell. These characteristics make the module high risk in general use and it can be abused for data exfiltration and remote command execution. If intended for legitimate remote support, additional protections are required: stronger key exchange, authenticated peers, allowlisting/sandboxing of filesystem access, logging/visibility, and operator confirmation before granting shell control.

[Skill Scanner] Pipe-to-shell or eval pattern detected All findings: [CRITICAL] command_injection: Pipe-to-shell or eval pattern detected (CI013) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] [CRITICAL] command_injection: Natural language instruction to download and install from URL detected (CI009) [AITech 9.1.4] This skill/instruction doc appears functionally legitimate and aligned with its stated purpose (YouTube thumbnail design using a remote inference CLI). However, it contains moderately high supply-chain risk patterns: a curl|sh installer that downloads and executes a CLI from inference.sh/dist.inference.sh, plus examples that send prompts and (potentially) images and authentication tokens to a third-party service. There are no hardcoded secrets or obfuscated code in the provided text. Recommend treating the installer pattern as risky: prefer pinned, auditable installs (manual checksum verification before execution), clear documentation on where credentials go, and least-privilege CLI invocation. Overall: no clear malware, but medium-to-high supply-chain/security risk due to download-and-execute and credential/ data-forwarding patterns. LLM verification: The SKILL.md is a benign thumbnail-design guide but instructs users to install and use a third-party CLI via a pipe-to-shell pattern and to authenticate that CLI. The immediate risks are supply-chain and credential exposure: executing a remote install script and sending prompts/files/credentials to external inference endpoints. There is no embedded malware in the text itself, but the recommended operational flow is high-risk. Recommendation: do not execute the pipe-to-shell installer without ind

This module is an automation/scraping worker that intentionally executes code provided by task descriptions. That design requires trusting the task source. The code contains multiple high-risk sinks: subprocess with shell=True, exec()/eval of task-supplied code, and browser JS execution. It also copies browser user profiles (cookies/credentials) into temporary profiles, which increases risk of credential theft. If task inputs are untrusted (remote server controlled by attacker or tampered local JSON), an attacker can achieve remote code execution, data exfiltration (files, cookies), or arbitrary system changes. Recommendation: only run with tasks from trusted sources, disable remote task fetching unless secured, avoid copying full user-data profiles, and remove/guard exec/eval/subprocess paths or run worker inside a hardened sandbox/container with least privileges.

The module itself is not obviously obfuscated or pre-packed with a secret backdoor, but it enables high-risk behavior: downloading/unzipping arbitrary content and executing it with shell=True, and extracting zip files unsafely. If an attacker can control ExecuteConfig (particularly exe_url, exe_path, exe_unzip_and_use, or command_suffix) or the downloaded resource, they can achieve remote code execution and arbitrary filesystem changes. Recommend treating this module as dangerous in untrusted contexts: enforce strict input validation, verify integrity/signatures of downloads, avoid shell=True by passing args as a list, sanitize zip entries before extractall, and implement cleanup of temp files.

Live on pypi for 2 hours and 44 minutes before removal. Socket users were protected even while the package was live.

The SweetAlert2 library code is mostly benign and serves as a UI modal dialog tool. However, it contains a suspicious and potentially malicious snippet that targets Russian users on certain domains to play an unsolicited audio prank, disabling pointer events and potentially disrupting user interaction. This behavior is unexpected and should be considered a moderate security risk and potential malware. The rest of the code shows no signs of malicious intent. The provided reports were invalid and unhelpful. Users should be cautious about this version of the library due to the embedded prank behavior.

This module is a high-risk remote-control/backdoor component: it exposes unauthenticated remote command execution (shell, exec, eval), arbitrary file upload and download, and background task creation. It should be treated as malicious/untrusted in most deployment contexts. Do not run this code on production or internet-accessible hosts. Immediate remediation: remove or quarantine the component, revoke any credentials/keys on the host, perform forensic audit for persistence or additional compromise, and block network access to any running instance.

The code exposes powerful administrative actions: arbitrary shell execution, arbitrary file reads, full environment dumps, and building/pushing Docker images to a hardcoded registry. These are not obfuscated but are high-risk capabilities that can be abused for data exfiltration, remote code execution, and supply-chain leakage if the superuser authentication is compromised or misconfigured. The presence of a hardcoded remote image name for docker push is suspicious for unintended outbound artifact exfiltration. Recommendation: avoid including these endpoints in public packages or ensure strict, auditable authentication and input validation; remove hardcoded push targets and avoid returning full environment variables or arbitrary file contents.

High-confidence malicious active data exfiltration: the script enumerates and base64-encodes all files under /opt and posts them to a hardcoded external webhook. Treat as confirmed compromise. Remove the code, block the destination domain, investigate systems that executed the module, rotate any credentials that may have been exposed, and perform forensic collection of affected hosts.

The OpenClaw and multi-source Tech News Digest footprint present a coherent workflow for aggregating, deduplicating, scoring, enriching, and delivering digests via multiple formats. However, the reliance on numerous environment-stored credentials, optional backends, and a prompt-driven orchestration introduces multiple risk vectors for secret leakage, supply-chain drift, and prompt-injection-like control if templates or prompts are improperly audited. The design is plausible for legitimate use but exhibits medium-to-high supply-chain risk due to credential management complexity, lack of explicit secret rotation, and broad outbound data flows. Recommended improvements include: adopting a centralized secret store with rotation policies, enforcing TLS pinning and strict back-end authentication defaults, implementing per-backend access controls and key rotation, adding explicit data minimization and consent policies, enabling script integrity verification (signing, hashing, pinned dependencies), and auditing the prompt templates (digest-prompt.md) for prompt-injection risk. Overall security risk remains moderate to high until mitigations are in place; malware likelihood remains low given no signs of payload delivery, but misconfigurations could enable data leakage or abuse.

This file is part of a malicious package that exploits software distribution infrastructure for social engineering attacks. The assembly metadata contains extensive promotional content advertising illegal Snapchat account hacking services, including detailed descriptions of traffic-based attack methods against Snapchat servers. The file directs users to visit an external malicious website at hacksgames[.]online/Snap-Hack/ through embedded URLs in assembly descriptions. While containing no executable malicious code (only empty class implementations), it serves as a delivery mechanism to redirect users to potentially harmful external sites that could distribute malware, conduct phishing attacks, or engage in other malicious activities. This represents supply chain pollution by abusing legitimate package repositories to promote illegal services and poses significant security risks to users who may follow the embedded malicious links.

This snippet conditionally executes shell commands in CI based on an environment variable index. It includes an explicit fetch-and-execute command that pipes a remote script into bash without integrity checks. Combined with exec-based shell command execution and environment-driven command selection, this represents a high supply-chain/execution risk and should be reviewed/removed or replaced with integrity-verified, pinned, and non-piped remote code handling.