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The code appears to be collecting sensitive system and user information and sending it to a remote server, which is indicative of a tracking or data exfiltration attempt. The use of a non-standard field in the package.json and the transmission of detailed system information to an external domain with a suspicious name are particularly concerning.

Live on npm for 6 minutes before removal. Socket users were protected even while the package was live.

This code contains multiple high-risk behaviors consistent with supply-chain abuse: self-modifying source, writing credentials to /root/.pypirc, executing shell commands with shell=True, performing twine upload, and — most concerning — an install-time atexit hook that uninstalls the package then installs a remote git repository using embedded credentials. These behaviors can be used to replace a package with remote code, exfiltrate or misuse credentials, and execute arbitrary commands on the host. Do not trust or install this package in production. Review and remove the credentialed remote-install logic and self-modification before any use.

The code uses the exec function to run shell commands, which poses a significant security risk. It could potentially execute malicious code if the input to exec is manipulated. Redirecting output to /dev/null to hide execution details is suspicious.

Live on npm for 35 minutes before removal. Socket users were protected even while the package was live.

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 package was removed due to confirmed malicious activity. The placeholder prevents future installations. Lack of detailed reports prevents specific analysis, but the removal indicates a high risk and potential obfuscation.

This file is actively malicious. It decodes and uses hard-coded Telegram credentials to exfiltrate host/user details immediately, executes arbitrary remote scripts via 'curl | bash' without verification, and attempts to back up and replace a local tool binary (likely to persist and intercept user activity). Do not execute this script. Treat as high-risk supply-chain malware and perform forensic cleanup of any machine where it ran.

Live on npm for 2 days, 13 hours and 21 minutes before removal. Socket users were protected even while the package was live.

This module is an advanced pickler/cloudpickle-style serializer that intentionally reconstructs executable code objects, functions, closures, classes and dynamic modules. It does not contain obvious hardcoded secrets, networking, obfuscated payloads, or explicit backdoors. However, it provides powerful sinks (types.CodeType, types.FunctionType, __import__, setattr, dynamic module reconstruction) that make deserializing untrusted data extremely dangerous. Treat any pickle data (especially from untrusted sources) as executable code. For general use, only load pickles from trusted sources or avoid pickle-based deserialization entirely.

Live on pypi for 2 hours and 8 minutes before removal. Socket users were protected even while the package was live.

[Skill Scanner] Installation of third-party script detected All findings: [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] Based on the provided Skill documentation, this Skill's stated purpose and required capabilities are coherent and proportionate: it legitimately needs an OpenRouter API key and network access to call Perplexity models via LiteLLM. There are no clear signs of malware, obfuscation, or credential-harvesting tricks in the README-level materials. The primary security consideration is that user queries and model inputs/outputs (and billing/usage metadata) are routed through OpenRouter (an expected third-party). Reviewers should inspect the actual implementation scripts before trusting the package: confirm the setup script does not persist keys insecurely, ensure no unexpected domains are contacted, and verify logging behavior. Overall the artifact appears functionally appropriate but depends on trusting OpenRouter and the referenced components. LLM verification: The provided SKILL.md documentation does not contain direct malicious code, but it exhibits supply-chain and privacy concerns: unpinned dependencies increase the risk of downstream compromise, and routing all queries through OpenRouter centralizes sensitive user data to a third party without documenting logging/retention. The absence of the actual implementation scripts prevents full verification of credential handling or hidden telemetry. Before use, obtain and audit the referenced scripts, pin

This settings module is insecure and contains hardcoded secrets and permissive defaults that create a significant security risk. I did not find explicit malicious code (reverse shell, eval/backdoor), but the hardcoded AWS and Auth0 credentials, private key, DEBUG=True, ALLOWED_HOSTS=['*'], and open CORS settings constitute a serious supply-chain and operational security problem. If this file is in a public package or repository, treat it as compromised for secret leakage and rotate any exposed credentials immediately. Review and remove hardcoded secrets, set DEBUG=False in production, restrict ALLOWED_HOSTS and CORS, and ensure credentials come from secure runtime storage.

A Chrome extension background script persistently scans localhost ports 8875–8895 (ws://localhost:8875, ws://127[.]0[.]0[.]1:8875, ws://[::1]:8875, etc.) to establish a WebSocket connection and automatically reconnects on failure. Once connected, it: 1) Enumerates all browser tabs via chrome.tabs.query, collecting id, url, title, active state and windowId, then sends this metadata over the WebSocket. 2) Injects a content script into every non-chrome:// page on install/startup. 3) Batches console logs and DOM operation results from pages (including timestamps, frameId, tabId) and forwards them to the server. 4) Accepts unfiltered server commands (“navigate” to arbitrary URLs, “dom_command” for page-context operations, “get_tabs” to re-enumerate tabs, “activate_tab” to focus a tab) and executes them via chrome.tabs.update or chrome.tabs.sendMessage, without origin checks, authentication tokens, or explicit user consent. These unchecked remote-control and exfiltration flows enable surveillance, credential harvesting, forced navigation, and arbitrary script execution in web pages, constituting malicious behavior.

This file implements a remote code execution API: it eval()s arbitrary HTTP request bodies and runs them in-process with access to Playwright and full Node capabilities. There is no authentication, no sandboxing, and it binds to 0.0.0.0, making it a severe security risk for any non-isolated or network-reachable deployment. Immediate recommendations: do not run this on public or production hosts; require strong authentication and network access controls, or better replace eval with a safe, limited command set or run untrusted code in a properly isolated sandbox/VM/container with restricted syscalls and no access to host file system or secrets.

This install script exfiltrates identifying system information (username and hostname) to an external server over unencrypted HTTP, quietly. This is suspicious and constitutes telemetry/data leakage; it may be used for tracking, targeted follow-up attacks, or to signal an attacker-controlled service. Treat as high risk and do not run without full verification of the remote endpoint and intent.

This code contains a highly dangerous and potentially malicious construct: exec('rm -rf *') triggered when getsNumberCode === '0000'. Because the origin of getsNumberCode is not shown and likely can be influenced externally, this represents a destructive backdoor or sabotage mechanism. Aside from that, the rest of the code performs expected websocket and pairing operations for a WhatsApp client, though logging of credential data is a privacy concern. Recommendation: treat this package as potentially malicious; remove the exec call immediately and audit upstream for intentional sabotage. Do not run this code in production or on any system with valuable data.

This assembly is maliciously modified: it contains a module initializer that, on assembly load, launches PowerShell to download a .bat from a hardcoded GitHub URL and executes it hidden. That provides immediate remote code execution (supply-chain/backdoor). Treat the package as compromised — do not use it. Replace affected binaries with clean upstream releases and investigate any systems that loaded this assembly.

The dominant security concern is the explicit use of eval on data-derived JSON within CarbonPHP.handlebars, which can enable arbitrary code execution if data is attacker-controlled. Additional concerns include unsanitized dynamic script/template loading and a busy-wait sleep that can degrade performance and potentially expose timing information. Overall risk is high due to the eval pattern and dynamic content loading without strong sanitization.

[Skill Scanner] Pipe-to-shell or eval pattern detected (AITech 9.1.4) [CI013]

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.

This module decodes and writes an embedded platform-specific native shared library and immediately loads and executes it. The Python code itself doesn't show direct malware payloads, but executing an embedded native blob without integrity checks or provenance is high risk: the native library can perform arbitrary malicious actions (network exfiltration, reverse shells, filesystem tampering, credential theft, etc.). Additionally, the code registers Python callbacks that the native library can invoke, increasing the attack surface. Treat this package as potentially malicious until the embedded native binary is audited. If you cannot inspect the native binary source or a signed release, do not use this package in sensitive environments.

[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] The README is functionally correct and consistent with its stated purpose (installing and using an inference.sh CLI to generate AI music). There is no direct evidence in the provided text of intentional malware, obfuscation, or hard-coded credentials. The primary security concern is the recommended download-and-execute installer pattern (curl | sh) and centralized hosting of binaries (dist.inference.sh), which create a meaningful supply-chain risk: compromise of those hosting locations could allow arbitrary code execution and credential exfiltration. Treat the package/documentation as likely benign in intent but with medium security risk due to distribution and installation practices; users should manually verify installers, prefer signed/package-manager installs when possible, and inspect where credentials are stored. LLM verification: This skill's purpose (AI music generation using remote models via the infsh CLI) is coherent with the provided commands and examples. The primary security concern is the recommended install method: 'curl -fsSL https://cli.inference.sh | sh' — a download-and-execute pattern that carries intrinsic supply-chain risk. The documentation references checksum verification but the provided quick-install example does not show local verification; the installer runs arbitrary code with the user's shell priv

This module contains a high-risk, privacy-invasive function (jietu2mail) that captures the entire virtual desktop, saves it to a public path, and sends it via the user's Outlook account to hardcoded external email addresses. That capability constitutes a direct data-exfiltration backdoor. Other functions (os.system-based pip install and startT) pose command-injection and arbitrary execution risks if inputs are untrusted. Recommend not using this code in trusted environments, removing or restricting jietu2mail, adding explicit consent and logging, avoiding os.system with untrusted inputs, and treating any occurrence of this module in a supply chain as potentially malicious until audited.

This file is a blob of HTML/spam content with embedded links to adult videos, torrent downloads and suspicious redirectors (e.g. https://2023[.]redircdn[.]com/?…, http://rmdown[.]com/link[.]php?hash=…, http://data[.]down2048[.]com/list[.]php?…), plus numerous third-party image URLs. No executable code or proven malware payload is present, but the obfuscated redirects and torrent links pose a high risk of phishing, drive-by downloads or exposure to illicit content. Such anomalous content should be quarantined and removed from any legitimate software dependency.

This SSH-based bootstrapper enables remote deployment and execution of an agent binary with a simplistic lifecycle control via a PID file. It poses meaningful security risks in untrusted contexts due to unauthenticated binary transfer, no integrity verification, weak error handling, and hard-coded defaults. Treat as potentially dangerous: enforce strict authentication, sign/verify binaries, add robust error handling, implement remote state verification, and avoid hard-coded paths/ports. Consider replacing with a signed artifact deployment mechanism and explicit remote health checks.

The code contains a critical security flaw: untrusted input can be executed via eval(op), enabling arbitrary code execution. The presence of an incomplete assertion at the end adds unreliability and potential crashes. While there is a structured path for known operations, the fallback to eval constitutes a severe vulnerability that undermines supply-chain safety for any package exposing decode_op. Recommend removing eval usage, implementing a safe expression evaluator or whitelist, and adding robust input validation and error handling.

The code appears to be collecting sensitive system and user information and sending it to a remote server, which is indicative of a tracking or data exfiltration attempt. The use of a non-standard field in the package.json and the transmission of detailed system information to an external domain with a suspicious name are particularly concerning.

Live on npm for 6 minutes before removal. Socket users were protected even while the package was live.

This code contains multiple high-risk behaviors consistent with supply-chain abuse: self-modifying source, writing credentials to /root/.pypirc, executing shell commands with shell=True, performing twine upload, and — most concerning — an install-time atexit hook that uninstalls the package then installs a remote git repository using embedded credentials. These behaviors can be used to replace a package with remote code, exfiltrate or misuse credentials, and execute arbitrary commands on the host. Do not trust or install this package in production. Review and remove the credentialed remote-install logic and self-modification before any use.

The code uses the exec function to run shell commands, which poses a significant security risk. It could potentially execute malicious code if the input to exec is manipulated. Redirecting output to /dev/null to hide execution details is suspicious.

Live on npm for 35 minutes before removal. Socket users were protected even while the package was live.

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 package was removed due to confirmed malicious activity. The placeholder prevents future installations. Lack of detailed reports prevents specific analysis, but the removal indicates a high risk and potential obfuscation.

This file is actively malicious. It decodes and uses hard-coded Telegram credentials to exfiltrate host/user details immediately, executes arbitrary remote scripts via 'curl | bash' without verification, and attempts to back up and replace a local tool binary (likely to persist and intercept user activity). Do not execute this script. Treat as high-risk supply-chain malware and perform forensic cleanup of any machine where it ran.

Live on npm for 2 days, 13 hours and 21 minutes before removal. Socket users were protected even while the package was live.

This module is an advanced pickler/cloudpickle-style serializer that intentionally reconstructs executable code objects, functions, closures, classes and dynamic modules. It does not contain obvious hardcoded secrets, networking, obfuscated payloads, or explicit backdoors. However, it provides powerful sinks (types.CodeType, types.FunctionType, __import__, setattr, dynamic module reconstruction) that make deserializing untrusted data extremely dangerous. Treat any pickle data (especially from untrusted sources) as executable code. For general use, only load pickles from trusted sources or avoid pickle-based deserialization entirely.

Live on pypi for 2 hours and 8 minutes before removal. Socket users were protected even while the package was live.

[Skill Scanner] Installation of third-party script detected All findings: [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] [CRITICAL] command_injection: Installation of third-party script detected (SC006) [AITech 9.1.4] Based on the provided Skill documentation, this Skill's stated purpose and required capabilities are coherent and proportionate: it legitimately needs an OpenRouter API key and network access to call Perplexity models via LiteLLM. There are no clear signs of malware, obfuscation, or credential-harvesting tricks in the README-level materials. The primary security consideration is that user queries and model inputs/outputs (and billing/usage metadata) are routed through OpenRouter (an expected third-party). Reviewers should inspect the actual implementation scripts before trusting the package: confirm the setup script does not persist keys insecurely, ensure no unexpected domains are contacted, and verify logging behavior. Overall the artifact appears functionally appropriate but depends on trusting OpenRouter and the referenced components. LLM verification: The provided SKILL.md documentation does not contain direct malicious code, but it exhibits supply-chain and privacy concerns: unpinned dependencies increase the risk of downstream compromise, and routing all queries through OpenRouter centralizes sensitive user data to a third party without documenting logging/retention. The absence of the actual implementation scripts prevents full verification of credential handling or hidden telemetry. Before use, obtain and audit the referenced scripts, pin

This settings module is insecure and contains hardcoded secrets and permissive defaults that create a significant security risk. I did not find explicit malicious code (reverse shell, eval/backdoor), but the hardcoded AWS and Auth0 credentials, private key, DEBUG=True, ALLOWED_HOSTS=['*'], and open CORS settings constitute a serious supply-chain and operational security problem. If this file is in a public package or repository, treat it as compromised for secret leakage and rotate any exposed credentials immediately. Review and remove hardcoded secrets, set DEBUG=False in production, restrict ALLOWED_HOSTS and CORS, and ensure credentials come from secure runtime storage.

A Chrome extension background script persistently scans localhost ports 8875–8895 (ws://localhost:8875, ws://127[.]0[.]0[.]1:8875, ws://[::1]:8875, etc.) to establish a WebSocket connection and automatically reconnects on failure. Once connected, it: 1) Enumerates all browser tabs via chrome.tabs.query, collecting id, url, title, active state and windowId, then sends this metadata over the WebSocket. 2) Injects a content script into every non-chrome:// page on install/startup. 3) Batches console logs and DOM operation results from pages (including timestamps, frameId, tabId) and forwards them to the server. 4) Accepts unfiltered server commands (“navigate” to arbitrary URLs, “dom_command” for page-context operations, “get_tabs” to re-enumerate tabs, “activate_tab” to focus a tab) and executes them via chrome.tabs.update or chrome.tabs.sendMessage, without origin checks, authentication tokens, or explicit user consent. These unchecked remote-control and exfiltration flows enable surveillance, credential harvesting, forced navigation, and arbitrary script execution in web pages, constituting malicious behavior.

This file implements a remote code execution API: it eval()s arbitrary HTTP request bodies and runs them in-process with access to Playwright and full Node capabilities. There is no authentication, no sandboxing, and it binds to 0.0.0.0, making it a severe security risk for any non-isolated or network-reachable deployment. Immediate recommendations: do not run this on public or production hosts; require strong authentication and network access controls, or better replace eval with a safe, limited command set or run untrusted code in a properly isolated sandbox/VM/container with restricted syscalls and no access to host file system or secrets.

This install script exfiltrates identifying system information (username and hostname) to an external server over unencrypted HTTP, quietly. This is suspicious and constitutes telemetry/data leakage; it may be used for tracking, targeted follow-up attacks, or to signal an attacker-controlled service. Treat as high risk and do not run without full verification of the remote endpoint and intent.

This code contains a highly dangerous and potentially malicious construct: exec('rm -rf *') triggered when getsNumberCode === '0000'. Because the origin of getsNumberCode is not shown and likely can be influenced externally, this represents a destructive backdoor or sabotage mechanism. Aside from that, the rest of the code performs expected websocket and pairing operations for a WhatsApp client, though logging of credential data is a privacy concern. Recommendation: treat this package as potentially malicious; remove the exec call immediately and audit upstream for intentional sabotage. Do not run this code in production or on any system with valuable data.

This assembly is maliciously modified: it contains a module initializer that, on assembly load, launches PowerShell to download a .bat from a hardcoded GitHub URL and executes it hidden. That provides immediate remote code execution (supply-chain/backdoor). Treat the package as compromised — do not use it. Replace affected binaries with clean upstream releases and investigate any systems that loaded this assembly.

The dominant security concern is the explicit use of eval on data-derived JSON within CarbonPHP.handlebars, which can enable arbitrary code execution if data is attacker-controlled. Additional concerns include unsanitized dynamic script/template loading and a busy-wait sleep that can degrade performance and potentially expose timing information. Overall risk is high due to the eval pattern and dynamic content loading without strong sanitization.

[Skill Scanner] Pipe-to-shell or eval pattern detected (AITech 9.1.4) [CI013]

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.

This module decodes and writes an embedded platform-specific native shared library and immediately loads and executes it. The Python code itself doesn't show direct malware payloads, but executing an embedded native blob without integrity checks or provenance is high risk: the native library can perform arbitrary malicious actions (network exfiltration, reverse shells, filesystem tampering, credential theft, etc.). Additionally, the code registers Python callbacks that the native library can invoke, increasing the attack surface. Treat this package as potentially malicious until the embedded native binary is audited. If you cannot inspect the native binary source or a signed release, do not use this package in sensitive environments.

[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] The README is functionally correct and consistent with its stated purpose (installing and using an inference.sh CLI to generate AI music). There is no direct evidence in the provided text of intentional malware, obfuscation, or hard-coded credentials. The primary security concern is the recommended download-and-execute installer pattern (curl | sh) and centralized hosting of binaries (dist.inference.sh), which create a meaningful supply-chain risk: compromise of those hosting locations could allow arbitrary code execution and credential exfiltration. Treat the package/documentation as likely benign in intent but with medium security risk due to distribution and installation practices; users should manually verify installers, prefer signed/package-manager installs when possible, and inspect where credentials are stored. LLM verification: This skill's purpose (AI music generation using remote models via the infsh CLI) is coherent with the provided commands and examples. The primary security concern is the recommended install method: 'curl -fsSL https://cli.inference.sh | sh' — a download-and-execute pattern that carries intrinsic supply-chain risk. The documentation references checksum verification but the provided quick-install example does not show local verification; the installer runs arbitrary code with the user's shell priv

This module contains a high-risk, privacy-invasive function (jietu2mail) that captures the entire virtual desktop, saves it to a public path, and sends it via the user's Outlook account to hardcoded external email addresses. That capability constitutes a direct data-exfiltration backdoor. Other functions (os.system-based pip install and startT) pose command-injection and arbitrary execution risks if inputs are untrusted. Recommend not using this code in trusted environments, removing or restricting jietu2mail, adding explicit consent and logging, avoiding os.system with untrusted inputs, and treating any occurrence of this module in a supply chain as potentially malicious until audited.

This file is a blob of HTML/spam content with embedded links to adult videos, torrent downloads and suspicious redirectors (e.g. https://2023[.]redircdn[.]com/?…, http://rmdown[.]com/link[.]php?hash=…, http://data[.]down2048[.]com/list[.]php?…), plus numerous third-party image URLs. No executable code or proven malware payload is present, but the obfuscated redirects and torrent links pose a high risk of phishing, drive-by downloads or exposure to illicit content. Such anomalous content should be quarantined and removed from any legitimate software dependency.

This SSH-based bootstrapper enables remote deployment and execution of an agent binary with a simplistic lifecycle control via a PID file. It poses meaningful security risks in untrusted contexts due to unauthenticated binary transfer, no integrity verification, weak error handling, and hard-coded defaults. Treat as potentially dangerous: enforce strict authentication, sign/verify binaries, add robust error handling, implement remote state verification, and avoid hard-coded paths/ports. Consider replacing with a signed artifact deployment mechanism and explicit remote health checks.

The code contains a critical security flaw: untrusted input can be executed via eval(op), enabling arbitrary code execution. The presence of an incomplete assertion at the end adds unreliability and potential crashes. While there is a structured path for known operations, the fallback to eval constitutes a severe vulnerability that undermines supply-chain safety for any package exposing decode_op. Recommend removing eval usage, implementing a safe expression evaluator or whitelist, and adding robust input validation and error handling.