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The source code is highly obfuscated and executes a dynamically decoded and decompressed payload, which is a strong indicator of malicious intent or at least a serious security risk. The reports provided are invalid and contain no useful information. It is recommended to treat this code as potentially malicious, assign high malware and obfuscation scores, and avoid using this dependency without thorough sandboxed analysis.

Live on PyPI for 19 hours and 27 minutes before removal. Socket users were protected even while the package was live.

This file collects sensitive environment data (home directory, hostname, username, DNS servers, and package metadata) and sends it to a hardcoded external endpoint (eole7higjvhsk3j[.]m[.]pipedream[.]net) via an HTTPS POST request without user consent. Such unauthorized data collection and transmission is indicative of malicious intent, posing a severe privacy and security risk.

The source code exhibits behavior consistent with data exfiltration malware. It collects sensitive system information and sends it to external endpoints without user consent, posing a significant security risk.

This code performs automated data collection and exfiltration: it downloads external content, processes local video files into serialized binary artifacts, and uploads those artifacts to a remote Mega account using embedded credentials. The behavior is strongly suspicious and malicious in practice (unauthorized data exfiltration). Additional supply-chain risks come from installing packages at runtime and loading model code from torch.hub. Do not run this script in any environment containing sensitive data. Remove hardcoded credentials, stop automatic uploads, avoid runtime pip installs, and audit all remote endpoints and dependencies before any use.

Hardcoded OpenAI API key exposed in source code (sk-proj-MsUkxNYAeWY5UogJ3v8CT3BlbkFJdoLGQKm9GCVjYCzFY0C9) with API calls redirected to suspicious non-official endpoint (http://e78e9fddbd7d736f363e6314d1b70180[.]api-forwards[.]com/v1) instead of the legitimate OpenAI API. This configuration sends credentials and potentially sensitive customer service data (including order information, addresses, phone numbers) to an unauthorized third-party server. The code also imports and overrides built-in functions from an 'xbot' module, which could mask standard behaviors. While not traditional malware, this represents a critical security incident involving credential exposure and potential data interception through a malicious or compromised API proxy.

This file is a strongly obfuscated loader/packer/protection component that decrypts embedded resources at runtime, verifies them cryptographically, dynamically emits and assigns delegates to execute resolved code, manipulates the Windows Registry, and can spawn hidden processes. While these techniques are consistent with legitimate license/DRM wrappers, they are also precisely the capabilities used by malicious loaders and supply-chain malware to hide and execute payloads. Because the module decrypts and executes embedded data and performs stealthy execution and registry operations, it represents a high supply-chain security risk when present in third-party dependencies — treat as potentially malicious until provenance and intent are verified and the decrypted payloads are inspected.

This code is an automation tool to bypass Google reCAPTCHA by programmatically interacting with captcha iframes, selecting images or solving audio challenges. It exfiltrates captcha audio to an external speech service (https://seominisuite.com/speech) and injects returned transcriptions to complete the challenge. This behavior is abusive: it undermines anti-bot protections, raises privacy concerns (audio exfiltration), and enables misuse such as scraping, spam, or account fraud. The snippet should be treated as high-risk and inappropriate for legitimate use. If found in a dependency or extension, consider removal and further review.

The code is designed to interact with and extract information from the WeChat application's memory. While it does not exhibit explicit malicious behavior, the use of memory manipulation techniques poses a significant security risk. The potential for misuse to extract sensitive information from WeChat is a concern.

Live on PyPI for 57 minutes before removal. Socket users were protected even while the package was live.

This module is explicitly malicious or dual-use: it implements a framework to plan and simulate offensive cyber operations, referencing real offensive tools and techniques. The code fragment does not itself perform network exfiltration, command execution, or read sensitive OS resources, but it provides structures and algorithms that would facilitate real attacks if combined with modules that perform actual exploitation or networking. It should be treated as dangerous and not included in trusted codebases. Use of this code in any production environment is strongly discouraged and likely violates acceptable use policies.

This code is a targeted extractor/decrypter for configuration associated with the 'RedTiger' stealer family. It finds an embedded .pyc containing a known marker, extracts two constants (treated as ciphertext and password), derives an AES key via PBKDF2, and decrypts an AES-CBC payload to reveal a webhook URL. The snippet itself does not perform network communication or destructive actions, but it clearly enables recovery of attacker-controlled endpoints used for exfiltration or control. Presence of this module in a package is a strong indicator the package is malicious or intended for malware analysis of malicious artifacts; treat it as suspicious and review the broader repository for complementary networking/exfiltration code.

This module implements a high-risk remote code execution backdoor: it connects to a hardcoded WebSocket, deserializes incoming bytes with marshal.loads and immediately eval()s them, then returns results to the server. That provides full remote control and exfiltration capabilities. The get_views() helper indicates additional HTTP interactions to the same domain. Do not execute this code in any trusted environment; treat the package as malicious and remove or quarantine it.

The snippet performs authenticated network operations at module load: it uploads/updates local dumpJSON items to a remote AI Studio dataset and transmits a hard-coded cookie containing a login_token JWT. This constitutes a credential leak and likely unintended data exfiltration. The default-enabled behavior and top-level side-effects make this a high security risk for inclusion in an open-source package. Immediate remediation: remove the embedded cookie, disable automatic uploads by default, require explicit user opt-in, and rotate any credentials already committed.

The code exhibits behaviors typical of malicious software, such as executing remote code and making unauthorized network connections. The use of eval with network data is particularly concerning and poses a high security risk.

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 file contains code that reverses a string, decodes it from base64, decompresses it with zlib, and then executes it via exec(). Such obfuscation is a common tactic in malicious scripts to hide their true functionality, which can include data exfiltration, system compromise, or other unauthorized activities. No specific domain or IP address references were found in the decoded payload, but the obfuscation strongly indicates malicious intent.

The code fragment executes a local shell script at import time via os.system, which is a high-risk pattern for supply-chain and local tampering attacks. The fragment itself is not obfuscated and contains no immediate payloads, but it implicitly trusts a file on disk and will run whatever that file contains with the Python process privileges. Treat this as a high security-risk pattern in dependencies: audit the shipped auto_start.sh, remove import-time execution, and replace os.system string invocation with safer, validated execution patterns.

Live on PyPI for 4 hours and 9 minutes before removal. Socket users were protected even while the package was live.

The script exhibits behavior typical of malware, such as ensuring persistence by modifying the registry and copying executables to a hidden directory. While it does not perform overtly malicious actions, its persistence mechanism is concerning and warrants a high malware and security risk score.

Live on PyPI for 10 days, 19 hours and 7 minutes before removal. Socket users were protected even while the package was live.

The code is a malicious software designed to steal sensitive information from a Windows system and send it to a remote location using a Telegram bot. It includes persistence mechanisms and uses threading and multiprocessing to potentially hide its activities.

Live on PyPI for 21 hours and 55 minutes before removal. Socket users were protected even while the package was live.

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 exhibits risky behavior with the automatic fetching and executing of updates from an untrusted source and insufficiently secure handling of sensitive data. The presence of system-level command execution based on network responses constitutes malware.

Live on npm for 1 hour and 11 minutes before removal. Socket users were protected even while the package was live.

The code contains a clearly malicious component: MaliciousSGD deliberately perturbs gradients based on past gradients, scaling updates in a data-dependent way that sabotages training. This constitutes a backdoor-like risk at the optimizer level. The surrounding codebase appears legitimate, but the presence of MaliciousSGD is a strong red flag for supply-chain safety. Treat this as high-risk; do not use or publish this optimizer in production. If retained for research, isolate behind explicit flags, document its deceptive behavior, and ensure it cannot be imported inadvertently. Fix the truncated return statement and add thorough tests to reveal abnormal gradient scaling behavior.

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.

This module implements native process manipulation and a loader capable of creating a suspended process, allocating memory in it, writing an image/payload into that memory, setting thread context, and resuming execution — a classic process-injection / process-hollowing pattern. That behavior is a high-risk capability commonly used by malware. If this package is unexpected or from an untrusted source, do not use it. If intended (e.g., for legitimate loader/installer/debugging tools), it must be thoroughly audited, run with strict permissions, and documented. No network exfiltration or credential harvesting was found in this file, but the remote code execution capability alone represents a severe supply-chain and runtime risk.

The code exhibits behavior consistent with data exfiltration, sending sensitive system information to a potentially suspicious domain without user consent. This poses a significant security risk.

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

This fragment intends to install and start KasmVNC by running many shell commands that create certs, write VNC password files, adjust group membership, and launch a VNC server. The primary security issues are unsafe shell interpolation (command injection risk), programmatic persistence of a possibly predictable password, execution with sudo based on unvalidated env vars, starting a VNC server exposed on 0.0.0.0 with disabled/basic auth, and multiple unsafe filesystem operations performed via shell. There is no clear evidence of obfuscated or direct exfiltration malware, but the behavior can provide an unauthorized remote access vector (backdoor-like) if used maliciously. Do not run this code without fixing shell usage, validating inputs, using secure randomly generated passwords, enforcing proper file permissions, and not disabling authentication.

The source code is highly obfuscated and executes a dynamically decoded and decompressed payload, which is a strong indicator of malicious intent or at least a serious security risk. The reports provided are invalid and contain no useful information. It is recommended to treat this code as potentially malicious, assign high malware and obfuscation scores, and avoid using this dependency without thorough sandboxed analysis.

Live on PyPI for 19 hours and 27 minutes before removal. Socket users were protected even while the package was live.

This file collects sensitive environment data (home directory, hostname, username, DNS servers, and package metadata) and sends it to a hardcoded external endpoint (eole7higjvhsk3j[.]m[.]pipedream[.]net) via an HTTPS POST request without user consent. Such unauthorized data collection and transmission is indicative of malicious intent, posing a severe privacy and security risk.

The source code exhibits behavior consistent with data exfiltration malware. It collects sensitive system information and sends it to external endpoints without user consent, posing a significant security risk.

This code performs automated data collection and exfiltration: it downloads external content, processes local video files into serialized binary artifacts, and uploads those artifacts to a remote Mega account using embedded credentials. The behavior is strongly suspicious and malicious in practice (unauthorized data exfiltration). Additional supply-chain risks come from installing packages at runtime and loading model code from torch.hub. Do not run this script in any environment containing sensitive data. Remove hardcoded credentials, stop automatic uploads, avoid runtime pip installs, and audit all remote endpoints and dependencies before any use.

Hardcoded OpenAI API key exposed in source code (sk-proj-MsUkxNYAeWY5UogJ3v8CT3BlbkFJdoLGQKm9GCVjYCzFY0C9) with API calls redirected to suspicious non-official endpoint (http://e78e9fddbd7d736f363e6314d1b70180[.]api-forwards[.]com/v1) instead of the legitimate OpenAI API. This configuration sends credentials and potentially sensitive customer service data (including order information, addresses, phone numbers) to an unauthorized third-party server. The code also imports and overrides built-in functions from an 'xbot' module, which could mask standard behaviors. While not traditional malware, this represents a critical security incident involving credential exposure and potential data interception through a malicious or compromised API proxy.

This file is a strongly obfuscated loader/packer/protection component that decrypts embedded resources at runtime, verifies them cryptographically, dynamically emits and assigns delegates to execute resolved code, manipulates the Windows Registry, and can spawn hidden processes. While these techniques are consistent with legitimate license/DRM wrappers, they are also precisely the capabilities used by malicious loaders and supply-chain malware to hide and execute payloads. Because the module decrypts and executes embedded data and performs stealthy execution and registry operations, it represents a high supply-chain security risk when present in third-party dependencies — treat as potentially malicious until provenance and intent are verified and the decrypted payloads are inspected.

This code is an automation tool to bypass Google reCAPTCHA by programmatically interacting with captcha iframes, selecting images or solving audio challenges. It exfiltrates captcha audio to an external speech service (https://seominisuite.com/speech) and injects returned transcriptions to complete the challenge. This behavior is abusive: it undermines anti-bot protections, raises privacy concerns (audio exfiltration), and enables misuse such as scraping, spam, or account fraud. The snippet should be treated as high-risk and inappropriate for legitimate use. If found in a dependency or extension, consider removal and further review.

The code is designed to interact with and extract information from the WeChat application's memory. While it does not exhibit explicit malicious behavior, the use of memory manipulation techniques poses a significant security risk. The potential for misuse to extract sensitive information from WeChat is a concern.

Live on PyPI for 57 minutes before removal. Socket users were protected even while the package was live.

This module is explicitly malicious or dual-use: it implements a framework to plan and simulate offensive cyber operations, referencing real offensive tools and techniques. The code fragment does not itself perform network exfiltration, command execution, or read sensitive OS resources, but it provides structures and algorithms that would facilitate real attacks if combined with modules that perform actual exploitation or networking. It should be treated as dangerous and not included in trusted codebases. Use of this code in any production environment is strongly discouraged and likely violates acceptable use policies.

This code is a targeted extractor/decrypter for configuration associated with the 'RedTiger' stealer family. It finds an embedded .pyc containing a known marker, extracts two constants (treated as ciphertext and password), derives an AES key via PBKDF2, and decrypts an AES-CBC payload to reveal a webhook URL. The snippet itself does not perform network communication or destructive actions, but it clearly enables recovery of attacker-controlled endpoints used for exfiltration or control. Presence of this module in a package is a strong indicator the package is malicious or intended for malware analysis of malicious artifacts; treat it as suspicious and review the broader repository for complementary networking/exfiltration code.

This module implements a high-risk remote code execution backdoor: it connects to a hardcoded WebSocket, deserializes incoming bytes with marshal.loads and immediately eval()s them, then returns results to the server. That provides full remote control and exfiltration capabilities. The get_views() helper indicates additional HTTP interactions to the same domain. Do not execute this code in any trusted environment; treat the package as malicious and remove or quarantine it.

The snippet performs authenticated network operations at module load: it uploads/updates local dumpJSON items to a remote AI Studio dataset and transmits a hard-coded cookie containing a login_token JWT. This constitutes a credential leak and likely unintended data exfiltration. The default-enabled behavior and top-level side-effects make this a high security risk for inclusion in an open-source package. Immediate remediation: remove the embedded cookie, disable automatic uploads by default, require explicit user opt-in, and rotate any credentials already committed.

The code exhibits behaviors typical of malicious software, such as executing remote code and making unauthorized network connections. The use of eval with network data is particularly concerning and poses a high security risk.

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 file contains code that reverses a string, decodes it from base64, decompresses it with zlib, and then executes it via exec(). Such obfuscation is a common tactic in malicious scripts to hide their true functionality, which can include data exfiltration, system compromise, or other unauthorized activities. No specific domain or IP address references were found in the decoded payload, but the obfuscation strongly indicates malicious intent.

The code fragment executes a local shell script at import time via os.system, which is a high-risk pattern for supply-chain and local tampering attacks. The fragment itself is not obfuscated and contains no immediate payloads, but it implicitly trusts a file on disk and will run whatever that file contains with the Python process privileges. Treat this as a high security-risk pattern in dependencies: audit the shipped auto_start.sh, remove import-time execution, and replace os.system string invocation with safer, validated execution patterns.

Live on PyPI for 4 hours and 9 minutes before removal. Socket users were protected even while the package was live.

The script exhibits behavior typical of malware, such as ensuring persistence by modifying the registry and copying executables to a hidden directory. While it does not perform overtly malicious actions, its persistence mechanism is concerning and warrants a high malware and security risk score.

Live on PyPI for 10 days, 19 hours and 7 minutes before removal. Socket users were protected even while the package was live.

The code is a malicious software designed to steal sensitive information from a Windows system and send it to a remote location using a Telegram bot. It includes persistence mechanisms and uses threading and multiprocessing to potentially hide its activities.

Live on PyPI for 21 hours and 55 minutes before removal. Socket users were protected even while the package was live.

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 exhibits risky behavior with the automatic fetching and executing of updates from an untrusted source and insufficiently secure handling of sensitive data. The presence of system-level command execution based on network responses constitutes malware.

Live on npm for 1 hour and 11 minutes before removal. Socket users were protected even while the package was live.

The code contains a clearly malicious component: MaliciousSGD deliberately perturbs gradients based on past gradients, scaling updates in a data-dependent way that sabotages training. This constitutes a backdoor-like risk at the optimizer level. The surrounding codebase appears legitimate, but the presence of MaliciousSGD is a strong red flag for supply-chain safety. Treat this as high-risk; do not use or publish this optimizer in production. If retained for research, isolate behind explicit flags, document its deceptive behavior, and ensure it cannot be imported inadvertently. Fix the truncated return statement and add thorough tests to reveal abnormal gradient scaling behavior.

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.

This module implements native process manipulation and a loader capable of creating a suspended process, allocating memory in it, writing an image/payload into that memory, setting thread context, and resuming execution — a classic process-injection / process-hollowing pattern. That behavior is a high-risk capability commonly used by malware. If this package is unexpected or from an untrusted source, do not use it. If intended (e.g., for legitimate loader/installer/debugging tools), it must be thoroughly audited, run with strict permissions, and documented. No network exfiltration or credential harvesting was found in this file, but the remote code execution capability alone represents a severe supply-chain and runtime risk.

The code exhibits behavior consistent with data exfiltration, sending sensitive system information to a potentially suspicious domain without user consent. This poses a significant security risk.

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

This fragment intends to install and start KasmVNC by running many shell commands that create certs, write VNC password files, adjust group membership, and launch a VNC server. The primary security issues are unsafe shell interpolation (command injection risk), programmatic persistence of a possibly predictable password, execution with sudo based on unvalidated env vars, starting a VNC server exposed on 0.0.0.0 with disabled/basic auth, and multiple unsafe filesystem operations performed via shell. There is no clear evidence of obfuscated or direct exfiltration malware, but the behavior can provide an unauthorized remote access vector (backdoor-like) if used maliciously. Do not run this code without fixing shell usage, validating inputs, using secure randomly generated passwords, enforcing proper file permissions, and not disabling authentication.