Secure your dependencies. Ship with confidence.

The code implements a file uploader that sends local files to a hardcoded external server without user consent or validation. This behavior constitutes a high security risk due to potential unauthorized data exfiltration. While the code is not obfuscated and contains no explicit malware payloads like backdoors or reverse shells, the act of uploading arbitrary files to an untrusted third-party domain is suspicious and likely malicious in a supply chain context. Users should avoid using this package as it poses a significant privacy and security threat.

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.

The file is a Torch/Pickle serialized model bundle (segmentation model + efficientnet encoder + weights) containing many binary pickles and debug metadata. I found no explicit plaintext backdoor indicators (hardcoded credentials, network endpoints, shell code) in the visible text, but this format (pickle/torch serialization) is inherently dangerous to load from untrusted sources because unpickling can execute arbitrary code. Recommendation: treat this as data only; do NOT load with torch.load or pickle.load in an untrusted environment. Verify provenance (checksums, signatures, trusted origin) and, when possible, load in a sandboxed environment or convert models via safer formats (e.g. ONNX with verified tooling) where applicable. If you must use torch.load, ensure it’s from a trusted source and consider loading map_location and strict options and run in isolated runtime.

The provided source code is not valid software code but a corrupted or maliciously injected blob containing adult content metadata and URLs. There is no executable code to analyze for malware, but the presence of inappropriate content indicates a severe supply chain compromise or injection attack. The reports are invalid and provide no security insights. This package should be rejected and flagged as highly suspicious and dangerous.

This script is a high-risk launcher: it unconditionally fetches Python code from a hardcoded remote repo and executes it locally via a shell-invoked Python process while passing unsanitized user inputs directly into the shell command. Even if the upstream repository is currently benign, the pattern enables trivial supply-chain compromise and shell injection. Mitigations: remove runtime download-and-exec; if fetching is necessary, pin and verify cryptographic hashes or signatures, validate content, avoid os.system (use subprocess with argument lists or importlib), sanitize inputs, and add error handling and logging. Treat this module as unsafe in security-sensitive environments until hardened.

The code poses a security risk due to the use of exec to perform a network request to an external URL. This could potentially be used for unauthorized data transmission or remote command execution. The lack of context or validation increases the risk of misuse.

Live on npm for 15 hours before removal. Socket users were protected even while the package was live.

The module contains multiple high-risk and malicious patterns: self-modifying source, embedded cleartext PyPI credentials, encrypted/hidden payloads restored and executed at runtime, widespread arbitrary shell execution built from untrusted inputs, and attempts to remove its own traces and to manipulate processes. Treat this package as malicious and unsafe for use in trusted environments. Immediate actions: do not install or run; isolate any systems that ran it; rotate any credentials that may have been written; perform a forensic review of files changed by the script; block associated accounts/domains and revoke PyPI credentials if used.

This fragment is spammy and potentially dangerous as content because it promotes downloads from untrusted hosts, redirector links, raw IP:port addresses, and services (VPNs, account sales). The fragment itself contains no executable code or direct backdoor, but it serves as a high-risk social-engineering vector: following links can lead to malware, credential theft, or fraud. If this HTML/text is bundled in a package (README, docs, or assets) it should be removed or sanitized. Do not click the provided links, and treat any included installers (APK/EXE/DMG) as untrusted until verified. Overall: not programmatic malware, but high security risk due to external links and content.

The code presents significant security risks due to the collection and transmission of sensitive system information and the use of hardcoded credentials. This behavior can be considered malicious if done without user consent.

Live on npm for 14 minutes before removal. Socket users were protected even while the package was live.

This code is a heavily-obfuscated mass-email/templating/sending module with features (proxy rotation, bulk SMTP, attachment obfuscation, automated conversion to multiple document formats, EML generation, and per-recipient templating using environment-derived fake details) that are commonly used for large-scale phishing or spam campaigns. No explicit system-level backdoor or reverse shell is visible in this fragment, but the combination of capabilities, deliberate obfuscation, and network-sending sinks makes it a high risk for misuse. Treat as potentially malicious in supply-chain contexts and audit the rest of the package and its dependencies before use.

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 code implements an insecure, unauthenticated RPC mechanism that allows remote clients to cause arbitrary code execution and exfiltrate files/system information. Using pickle over an untrusted network and invoking methods by client-supplied names are severe supply-chain/backdoor risks. Do not deploy or reuse this code in production; it should be treated as a backdoor/untrusted remote-execution component unless wrapped with strong authentication, authorization, sandboxing, and safe serialization.

The code is intentionally obfuscated and implements a runtime loader that decrypts embedded data and performs native memory allocation, writing, protection changes, and execution via delegates/func-pointers. It also includes process/module enumeration and multiple low-level native API calls (VirtualAlloc, WriteProcessMemory, VirtualProtect, LoadLibrary/GetProcAddress). These are strong indicators of an in-memory loader/injector/payload runner. This behavior is highly suspicious for an open-source dependency and represents a serious supply-chain risk unless the package's purpose explicitly requires such functionality (which is uncommon). Recommend not using this package and performing full dynamic analysis / provenance review if needed.

The flagged file exports a function named `isvalidkey` that, instead of validating input, unconditionally sends its argument to a hardcoded Telegram bot API endpoint (https://api[.]telegram[.]org/bot8156914790:AAHNd2ytOGqd_nC10BP64O2Z_Lx5nLXRb8E/sendMessage) with chat_id `-1003084751087`. Errors from the network call are silently ignored, and the function always returns true. Any data passed—including API keys, passwords, or environment variables—will be exfiltrated to a Telegram chat controlled by the attacker. This constitutes a backdoor and supply-chain malware that can leak sensitive information without user consent.

The code exhibits behavior typical of malware, specifically designed to collect and exfiltrate sensitive system information through DNS queries to a suspicious domain. This poses a significant security risk.

This code is intentionally obfuscated and uses DNS queries to exfiltrate system information, which could be a significant security risk. The hardcoded domain and the potential data exfiltration raise concerns about privacy violations. This package should be reviewed carefully before being used.

The fragment contains a high-risk pattern: it downloads a Python script from a remote source and immediately executes it without integrity verification or sandboxing. This creates a critical supply-chain and remote-code-execution risk, as the remote payload could perform any action on the host, including data exfiltration, credential access, or system compromise. Even though defaults use placeholders, the mechanism itself is unsafe and should be disallowed or hardened (e.g., verify hashes, use signed modules, avoid executing remote code).

This module is an LLM-driven orchestrator that exposes powerful actions (shell execution, GitHub repo modifications, working-directory changes) directly to a model without visible safeguards. The file is syntactically incomplete, but the design is high-risk: a compromised model, malicious prompt, or inadvertent instruction could trigger arbitrary command execution, repository tampering, or leakage of secrets via printed tool outputs. There is no direct evidence of embedded malware or obfuscation in this snippet, but running this code as-is (or completing it) in a privileged environment would be unsafe without strict mitigations: sandboxing, credential scoping, human authorization, command allowlists, output redaction, and audit logging.

This module implements covert telemetry/exfiltration: it silently collects local username and IP-based location and uploads daily aggregated records to a hardcoded GitHub repository. That behavior is privacy-invasive and constitutes a supply-chain risk for consumers of the package. The implementation uses weak obfuscation (base64), brittle JSON handling, and swallows exceptions, increasing the likelihood of stealthy, unintended data leakage. Actionable advice: treat this as malicious/unwanted telemetry unless documented explicit opt-in exists; remove or disable the telemetry code, or require explicit user consent and secure the transport (authentication and encryption), and fix robust JSON/file handling and error reporting before use.

This script is a high-risk launcher: it unconditionally fetches Python code from a hardcoded remote repo and executes it locally via a shell-invoked Python process while passing unsanitized user inputs directly into the shell command. Even if the upstream repository is currently benign, the pattern enables trivial supply-chain compromise and shell injection. Mitigations: remove runtime download-and-exec; if fetching is necessary, pin and verify cryptographic hashes or signatures, validate content, avoid os.system (use subprocess with argument lists or importlib), sanitize inputs, and add error handling and logging. Treat this module as unsafe in security-sensitive environments until hardened.

This assembly contains a legitimate-looking PLC WPF UI component, but also a separate, heavily obfuscated module that decrypts embedded resources and provides runtime code-loading and low-level native process memory operations (VirtualAlloc, WriteProcessMemory, VirtualProtect, OpenProcess). Those capabilities are typical of in-memory loaders, process injectors, or backdoors. Given the combination of obfuscation, encrypted resources, dynamic method creation and direct native memory write APIs, this code is highly suspicious and likely malicious or at least contains functionality outside expected behavior for a UI PLC library. I recommend not using this package and conducting a deeper dynamic/runtime analysis (sandbox execution, unpack the embedded resources, inspect decrypted payloads) and checking package provenance.

This code is malicious: it injects attacker-controlled HTML to present a phishing login form, captures plaintext credentials and session cookies, exfiltrates them to an attacker-controlled ngrok WebSocket, and redirects the user afterward. It constitutes credential and session theft and should be treated as a high-risk backdoor/phishing artifact. Remove and block the code and the remote endpoints, and investigate any exposed credentials or sessions.

Live on npm for 15 minutes before removal. Socket users were protected even while the package was live.

The code implements a file uploader that sends local files to a hardcoded external server without user consent or validation. This behavior constitutes a high security risk due to potential unauthorized data exfiltration. While the code is not obfuscated and contains no explicit malware payloads like backdoors or reverse shells, the act of uploading arbitrary files to an untrusted third-party domain is suspicious and likely malicious in a supply chain context. Users should avoid using this package as it poses a significant privacy and security threat.

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.

The file is a Torch/Pickle serialized model bundle (segmentation model + efficientnet encoder + weights) containing many binary pickles and debug metadata. I found no explicit plaintext backdoor indicators (hardcoded credentials, network endpoints, shell code) in the visible text, but this format (pickle/torch serialization) is inherently dangerous to load from untrusted sources because unpickling can execute arbitrary code. Recommendation: treat this as data only; do NOT load with torch.load or pickle.load in an untrusted environment. Verify provenance (checksums, signatures, trusted origin) and, when possible, load in a sandboxed environment or convert models via safer formats (e.g. ONNX with verified tooling) where applicable. If you must use torch.load, ensure it’s from a trusted source and consider loading map_location and strict options and run in isolated runtime.

The provided source code is not valid software code but a corrupted or maliciously injected blob containing adult content metadata and URLs. There is no executable code to analyze for malware, but the presence of inappropriate content indicates a severe supply chain compromise or injection attack. The reports are invalid and provide no security insights. This package should be rejected and flagged as highly suspicious and dangerous.

This script is a high-risk launcher: it unconditionally fetches Python code from a hardcoded remote repo and executes it locally via a shell-invoked Python process while passing unsanitized user inputs directly into the shell command. Even if the upstream repository is currently benign, the pattern enables trivial supply-chain compromise and shell injection. Mitigations: remove runtime download-and-exec; if fetching is necessary, pin and verify cryptographic hashes or signatures, validate content, avoid os.system (use subprocess with argument lists or importlib), sanitize inputs, and add error handling and logging. Treat this module as unsafe in security-sensitive environments until hardened.

The code poses a security risk due to the use of exec to perform a network request to an external URL. This could potentially be used for unauthorized data transmission or remote command execution. The lack of context or validation increases the risk of misuse.

Live on npm for 15 hours before removal. Socket users were protected even while the package was live.

The module contains multiple high-risk and malicious patterns: self-modifying source, embedded cleartext PyPI credentials, encrypted/hidden payloads restored and executed at runtime, widespread arbitrary shell execution built from untrusted inputs, and attempts to remove its own traces and to manipulate processes. Treat this package as malicious and unsafe for use in trusted environments. Immediate actions: do not install or run; isolate any systems that ran it; rotate any credentials that may have been written; perform a forensic review of files changed by the script; block associated accounts/domains and revoke PyPI credentials if used.

This fragment is spammy and potentially dangerous as content because it promotes downloads from untrusted hosts, redirector links, raw IP:port addresses, and services (VPNs, account sales). The fragment itself contains no executable code or direct backdoor, but it serves as a high-risk social-engineering vector: following links can lead to malware, credential theft, or fraud. If this HTML/text is bundled in a package (README, docs, or assets) it should be removed or sanitized. Do not click the provided links, and treat any included installers (APK/EXE/DMG) as untrusted until verified. Overall: not programmatic malware, but high security risk due to external links and content.

The code presents significant security risks due to the collection and transmission of sensitive system information and the use of hardcoded credentials. This behavior can be considered malicious if done without user consent.

Live on npm for 14 minutes before removal. Socket users were protected even while the package was live.

This code is a heavily-obfuscated mass-email/templating/sending module with features (proxy rotation, bulk SMTP, attachment obfuscation, automated conversion to multiple document formats, EML generation, and per-recipient templating using environment-derived fake details) that are commonly used for large-scale phishing or spam campaigns. No explicit system-level backdoor or reverse shell is visible in this fragment, but the combination of capabilities, deliberate obfuscation, and network-sending sinks makes it a high risk for misuse. Treat as potentially malicious in supply-chain contexts and audit the rest of the package and its dependencies before use.

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 code implements an insecure, unauthenticated RPC mechanism that allows remote clients to cause arbitrary code execution and exfiltrate files/system information. Using pickle over an untrusted network and invoking methods by client-supplied names are severe supply-chain/backdoor risks. Do not deploy or reuse this code in production; it should be treated as a backdoor/untrusted remote-execution component unless wrapped with strong authentication, authorization, sandboxing, and safe serialization.

The code is intentionally obfuscated and implements a runtime loader that decrypts embedded data and performs native memory allocation, writing, protection changes, and execution via delegates/func-pointers. It also includes process/module enumeration and multiple low-level native API calls (VirtualAlloc, WriteProcessMemory, VirtualProtect, LoadLibrary/GetProcAddress). These are strong indicators of an in-memory loader/injector/payload runner. This behavior is highly suspicious for an open-source dependency and represents a serious supply-chain risk unless the package's purpose explicitly requires such functionality (which is uncommon). Recommend not using this package and performing full dynamic analysis / provenance review if needed.

The flagged file exports a function named `isvalidkey` that, instead of validating input, unconditionally sends its argument to a hardcoded Telegram bot API endpoint (https://api[.]telegram[.]org/bot8156914790:AAHNd2ytOGqd_nC10BP64O2Z_Lx5nLXRb8E/sendMessage) with chat_id `-1003084751087`. Errors from the network call are silently ignored, and the function always returns true. Any data passed—including API keys, passwords, or environment variables—will be exfiltrated to a Telegram chat controlled by the attacker. This constitutes a backdoor and supply-chain malware that can leak sensitive information without user consent.

The code exhibits behavior typical of malware, specifically designed to collect and exfiltrate sensitive system information through DNS queries to a suspicious domain. This poses a significant security risk.

This code is intentionally obfuscated and uses DNS queries to exfiltrate system information, which could be a significant security risk. The hardcoded domain and the potential data exfiltration raise concerns about privacy violations. This package should be reviewed carefully before being used.

The fragment contains a high-risk pattern: it downloads a Python script from a remote source and immediately executes it without integrity verification or sandboxing. This creates a critical supply-chain and remote-code-execution risk, as the remote payload could perform any action on the host, including data exfiltration, credential access, or system compromise. Even though defaults use placeholders, the mechanism itself is unsafe and should be disallowed or hardened (e.g., verify hashes, use signed modules, avoid executing remote code).

This module is an LLM-driven orchestrator that exposes powerful actions (shell execution, GitHub repo modifications, working-directory changes) directly to a model without visible safeguards. The file is syntactically incomplete, but the design is high-risk: a compromised model, malicious prompt, or inadvertent instruction could trigger arbitrary command execution, repository tampering, or leakage of secrets via printed tool outputs. There is no direct evidence of embedded malware or obfuscation in this snippet, but running this code as-is (or completing it) in a privileged environment would be unsafe without strict mitigations: sandboxing, credential scoping, human authorization, command allowlists, output redaction, and audit logging.

This module implements covert telemetry/exfiltration: it silently collects local username and IP-based location and uploads daily aggregated records to a hardcoded GitHub repository. That behavior is privacy-invasive and constitutes a supply-chain risk for consumers of the package. The implementation uses weak obfuscation (base64), brittle JSON handling, and swallows exceptions, increasing the likelihood of stealthy, unintended data leakage. Actionable advice: treat this as malicious/unwanted telemetry unless documented explicit opt-in exists; remove or disable the telemetry code, or require explicit user consent and secure the transport (authentication and encryption), and fix robust JSON/file handling and error reporting before use.

This script is a high-risk launcher: it unconditionally fetches Python code from a hardcoded remote repo and executes it locally via a shell-invoked Python process while passing unsanitized user inputs directly into the shell command. Even if the upstream repository is currently benign, the pattern enables trivial supply-chain compromise and shell injection. Mitigations: remove runtime download-and-exec; if fetching is necessary, pin and verify cryptographic hashes or signatures, validate content, avoid os.system (use subprocess with argument lists or importlib), sanitize inputs, and add error handling and logging. Treat this module as unsafe in security-sensitive environments until hardened.

This assembly contains a legitimate-looking PLC WPF UI component, but also a separate, heavily obfuscated module that decrypts embedded resources and provides runtime code-loading and low-level native process memory operations (VirtualAlloc, WriteProcessMemory, VirtualProtect, OpenProcess). Those capabilities are typical of in-memory loaders, process injectors, or backdoors. Given the combination of obfuscation, encrypted resources, dynamic method creation and direct native memory write APIs, this code is highly suspicious and likely malicious or at least contains functionality outside expected behavior for a UI PLC library. I recommend not using this package and conducting a deeper dynamic/runtime analysis (sandbox execution, unpack the embedded resources, inspect decrypted payloads) and checking package provenance.

This code is malicious: it injects attacker-controlled HTML to present a phishing login form, captures plaintext credentials and session cookies, exfiltrates them to an attacker-controlled ngrok WebSocket, and redirects the user afterward. It constitutes credential and session theft and should be treated as a high-risk backdoor/phishing artifact. Remove and block the code and the remote endpoints, and investigate any exposed credentials or sessions.

Live on npm for 15 minutes before removal. Socket users were protected even while the package was live.