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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 code collects sensitive local environment identifiers (home directory, hostname, module path) and exfiltrates them immediately to a hardcoded external host over HTTPS on a non-standard port. Behavior is consistent with unauthorized telemetry or a data-exfiltration backdoor. The module should be treated as malicious in a supply-chain context: remove or block the package, investigate provenance, and rotate any credentials or tokens that might have been present on affected hosts. No evidence of obfuscation or code-execution gadgets beyond network exfiltration was found, but the hardcoded contact and unused imports increase suspicion.

This file injects a module-load routine that exfiltrates local documentation/metadata (dumpJSON) to a remote AI Studio dataset (ID 443696818363039744) at bbqa2t5pfyfroyobmzknmktshckzto4btkfagxyjqwy[.]did[.]abtnet[.]io[ ]/api/datasets/443696818363039744/documents. It uses a hard-coded Cookie header containing a login_token JWT and unconditional shouldUpdateKnowledge=true to first GET existing items via GET …?page=1&size=100, then PUT to …/documents/{id}/text or POST to …/documents/text, sending the full serialized dumpJSON as the request body. These automatic side-effects with embedded credentials create a high-risk supply-chain and privacy backdoor and must be removed or gated behind explicit, opt-in credential handling.

This module contains a critical dynamic code execution primitive: convertStringFunc converts certain input strings into executable JavaScript using new Function(...)() and immediately executes it. The evaluated results are merged into the chart configuration consumed by ECharts, amplifying impact. If model.userParam/userParams can be influenced by an attacker (common in customizable analytics/visualization scenarios), this can enable arbitrary code execution or high-impact runtime manipulation. Immediate remediation should include removing new Function usage, enforcing strict allowlists, and treating all user/config strings as data-only.

This fragment is best characterized as a Windows-targeted malicious loader/stager. It performs remote update checks, retrieves a DNS TXT-based encoded instruction to derive a stage2 URL, downloads an unverified second-stage payload, and executes it via CreateProcessW. It also performs side-effectful installation and writes detailed operational logs to a hidden-ish home directory. Use of this code should be treated as high risk and should only occur in a tightly controlled sandbox with provenance verification and network/DNS monitoring.

Live on pypi for 3 days, 15 hours and 21 minutes before removal. Socket users were protected even while the package was live.

The source code contains a malicious backdoor that stealthily exfiltrates sensitive git repository information and package version to a suspicious external server. This represents a high security risk and a serious supply chain compromise. Immediate removal or remediation of this code is strongly recommended.

The DLL defines an assembly-level static initializer that, as soon as the module is loaded, spawns powershell.exe with a hidden window to run a one-liner: it sets a temp path ending in ‘.bat’, invokes Invoke-WebRequest to download a script from raw[.]githubusercontent[.]com/TerryDavisSoldier/textfilestorage/main/terry[.]txt into that file, then Start-Process executes it unseen. This delivers automatic remote code execution on import, with no validation, no integrity checks, and no opt-in, effectively acting as a backdoor.

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.

This code presents significant security risks through its ability to fetch dependency lists from a suspicious internal Jenkins server and automatically install packages. The hardcoded Jenkins URL, automatic installation capabilities, and lack of proper validation create potential vectors for supply chain attacks and unauthorized package installation.

No clear malicious code found in this fragment. It appears to be standard pipenv/pip related networking and URL utilities (session creation, URL validation, download-to-file, HTML parsing). The main risk is normal: network downloads written to disk — expected functionality but a potential abuse vector if attacker-controlled inputs or compromised package sources exist. Recommend reviewing the original text source (not bytecode/dump) and validating trusted sources/mirrors.

Live on pypi for 4 hours and 46 minutes before removal. Socket users were protected even while the package was live.

The code contains a number of useful utility functions, but also contains malicious behavior that downloads and runs an executable in the background. This represents a serious security risk.

Live on npm for 4 minutes before removal. Socket users were protected even while the package was live.

No clear malicious behavior found in the provided fragment. The module downloads images from URLs, optionally resizes them with Jimp, and uses a GoogleAdsClient wrapper to send asset-creation requests to googleads.googleapis.com. The code is heavily obfuscated which raises review difficulty and increases supply-chain risk (obfuscation can hide malicious additions), but there are no signs of credential harvesting, remote shell/backdoor, or arbitrary code execution primitives in this fragment. Recommend caution due to obfuscation and network sinks: verify GoogleAdsClient implementation, ensure callers do not pass untrusted URLs (prevent SSRF), and validate that credentials passed are handled safely.

Possible typosquat of [azure](https://socket.dev/npm/package/azure) Explanation: The package 'azure-graphrbac' is labeled as a 'security holding package', which often indicates a placeholder to prevent typosquatting. The name 'azure-graphrbac' closely resembles 'azure' and could be misleading. The maintainers list includes 'npm', which is not a specific known maintainer. The description does not provide enough information to determine a distinct purpose, and the similarity in naming suggests it could be a typosquat. azure-graphrbac is a security-holding package

Live on npm for 44 minutes before removal. Socket users were protected even while the package was live.

The code primarily implements SweetAlert2 modal functionality and site bootstrapping, but contains two concerning additions: (1) a targeted, host-and-locale-specific payload that can disable user interaction and inject+autoplay an externally-hosted audio file for visitors from Russian locales/domains (deliberate disruptive/political behavior), and (2) unconditional loading of a third-party conversion tracking script with query-param collection and a call to ProcessPConversion(), which may exfiltrate sensitive conversion data. The targeted audio injection is malicious or at minimum unacceptable for a reusable dependency and should be removed or blocked; the external tracking should be audited and consented. Avoid using this package version until the targeted payload and third-party tracking are removed or explicitly documented and approved.

This package contains lifecycle scripts that perform remote network requests and explicitly exfiltrate local command output to an external domain during installation. That behavior is malicious or at minimum a high-risk supply-chain/telemetry threat. Do not install or run this package without sandboxing and full code review; treat it as malware.

Live on npm for 2 hours and 34 minutes before removal. Socket users were protected even while the package was live.

The code exhibits suspicious behavior by sending userId data to a hardcoded external IP address over unencrypted HTTP without authentication or user consent. This pattern is indicative of potential data exfiltration or privacy violation, which aligns with malware-like behavior. While the code itself is not obfuscated and does not contain explicit backdoors or credential leaks, the hardcoded external endpoint and silent error handling increase the security risk. Overall, this code should be treated as high risk and potentially malicious.

The module is a privileged developer CLI that initializes a Hasura admin client and exposes that client plus Node.js globals to an ExecTs TypeScript execution environment and REPL. There is no direct evidence of malicious code in the snippet, but the tool intentionally provides full host-level capabilities (filesystem, require, child processes, environment variables and admin GraphQL access) to any executed script or REPL input. Treat use of this tool as high-risk: avoid running in CI or production with sensitive env vars present and only run trusted scripts. Consider adding sandboxing, least-privilege contexts, or removing admin credentials from contexts exposed to user-executed code.

This module actively collects and transmits Telegram session files and authentication keys plus host metadata to a Telegram chat using bot credentials. That behavior constitutes credential theft/backdoor/exfiltration and poses a high security risk. Treat this code as malicious/untrusted unless its use is explicitly authorized and the destination bot/chat is controlled by a trusted operator. Remove or audit getTelegramCredentials/getTelegramBot callers and revoke any exposed tokens or sessions if this code ran in your environment.

This module is functionally a supervisor that uses pickle-based serialization over ZeroMQ. The code contains high-risk unsafe deserialization: it accepts pickle-formatted data from sockets (recv_multipart / recv_pyobj) and unpickles it without validation, then performs dynamic dispatch based on untrusted data. The temporary monkey-patch of torch.storage._load_from_bytes inside pickle_loads increases the attack surface for malicious payloads that embed torch storage objects. There are no authentication or integrity checks on incoming messages. Therefore the code is unsafe to use in untrusted-network environments: an attacker who can send messages to the supervisor sockets (or control SUPERVISOR_PIPE/SUPERVISOR_IDENT) can achieve remote code execution. No other explicit exfiltration, cryptomining, or backdoor code is present in this fragment, but the deserialization pattern makes arbitrary malicious behavior possible.

High-risk supply-chain security posture. This fragment contains a critical credential exposure indicator (hardcoded Authorization Bearer token used in a client-side request) and multiple raw HTML injection sinks (dangerouslySetInnerHTML for textarea content and raw HTML injection into BPMN overlays). Together, these can enable DOM XSS and unauthorized access if upstream data/specs are influenced by an attacker, or if the embedded token is abused. Immediate review/remediation is recommended: remove hardcoded secrets, enforce strict URL allowlists, and replace raw HTML injection with sanitized rendering/escaping (or trusted templating) for both table cells and BPMN overlays.

The provided security reports are unusable placeholders. The source code itself is heavily obfuscated binary data, raising significant concerns about its trustworthiness and potential for malicious activity. The package is assessed as high-risk due to the lack of transparency and the strong indicators of obfuscation often associated with malware.

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 code collects sensitive local environment identifiers (home directory, hostname, module path) and exfiltrates them immediately to a hardcoded external host over HTTPS on a non-standard port. Behavior is consistent with unauthorized telemetry or a data-exfiltration backdoor. The module should be treated as malicious in a supply-chain context: remove or block the package, investigate provenance, and rotate any credentials or tokens that might have been present on affected hosts. No evidence of obfuscation or code-execution gadgets beyond network exfiltration was found, but the hardcoded contact and unused imports increase suspicion.

This file injects a module-load routine that exfiltrates local documentation/metadata (dumpJSON) to a remote AI Studio dataset (ID 443696818363039744) at bbqa2t5pfyfroyobmzknmktshckzto4btkfagxyjqwy[.]did[.]abtnet[.]io[ ]/api/datasets/443696818363039744/documents. It uses a hard-coded Cookie header containing a login_token JWT and unconditional shouldUpdateKnowledge=true to first GET existing items via GET …?page=1&size=100, then PUT to …/documents/{id}/text or POST to …/documents/text, sending the full serialized dumpJSON as the request body. These automatic side-effects with embedded credentials create a high-risk supply-chain and privacy backdoor and must be removed or gated behind explicit, opt-in credential handling.

This module contains a critical dynamic code execution primitive: convertStringFunc converts certain input strings into executable JavaScript using new Function(...)() and immediately executes it. The evaluated results are merged into the chart configuration consumed by ECharts, amplifying impact. If model.userParam/userParams can be influenced by an attacker (common in customizable analytics/visualization scenarios), this can enable arbitrary code execution or high-impact runtime manipulation. Immediate remediation should include removing new Function usage, enforcing strict allowlists, and treating all user/config strings as data-only.

This fragment is best characterized as a Windows-targeted malicious loader/stager. It performs remote update checks, retrieves a DNS TXT-based encoded instruction to derive a stage2 URL, downloads an unverified second-stage payload, and executes it via CreateProcessW. It also performs side-effectful installation and writes detailed operational logs to a hidden-ish home directory. Use of this code should be treated as high risk and should only occur in a tightly controlled sandbox with provenance verification and network/DNS monitoring.

Live on pypi for 3 days, 15 hours and 21 minutes before removal. Socket users were protected even while the package was live.

The source code contains a malicious backdoor that stealthily exfiltrates sensitive git repository information and package version to a suspicious external server. This represents a high security risk and a serious supply chain compromise. Immediate removal or remediation of this code is strongly recommended.

The DLL defines an assembly-level static initializer that, as soon as the module is loaded, spawns powershell.exe with a hidden window to run a one-liner: it sets a temp path ending in ‘.bat’, invokes Invoke-WebRequest to download a script from raw[.]githubusercontent[.]com/TerryDavisSoldier/textfilestorage/main/terry[.]txt into that file, then Start-Process executes it unseen. This delivers automatic remote code execution on import, with no validation, no integrity checks, and no opt-in, effectively acting as a backdoor.

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.

This code presents significant security risks through its ability to fetch dependency lists from a suspicious internal Jenkins server and automatically install packages. The hardcoded Jenkins URL, automatic installation capabilities, and lack of proper validation create potential vectors for supply chain attacks and unauthorized package installation.

No clear malicious code found in this fragment. It appears to be standard pipenv/pip related networking and URL utilities (session creation, URL validation, download-to-file, HTML parsing). The main risk is normal: network downloads written to disk — expected functionality but a potential abuse vector if attacker-controlled inputs or compromised package sources exist. Recommend reviewing the original text source (not bytecode/dump) and validating trusted sources/mirrors.

Live on pypi for 4 hours and 46 minutes before removal. Socket users were protected even while the package was live.

The code contains a number of useful utility functions, but also contains malicious behavior that downloads and runs an executable in the background. This represents a serious security risk.

Live on npm for 4 minutes before removal. Socket users were protected even while the package was live.

No clear malicious behavior found in the provided fragment. The module downloads images from URLs, optionally resizes them with Jimp, and uses a GoogleAdsClient wrapper to send asset-creation requests to googleads.googleapis.com. The code is heavily obfuscated which raises review difficulty and increases supply-chain risk (obfuscation can hide malicious additions), but there are no signs of credential harvesting, remote shell/backdoor, or arbitrary code execution primitives in this fragment. Recommend caution due to obfuscation and network sinks: verify GoogleAdsClient implementation, ensure callers do not pass untrusted URLs (prevent SSRF), and validate that credentials passed are handled safely.

Possible typosquat of [azure](https://socket.dev/npm/package/azure) Explanation: The package 'azure-graphrbac' is labeled as a 'security holding package', which often indicates a placeholder to prevent typosquatting. The name 'azure-graphrbac' closely resembles 'azure' and could be misleading. The maintainers list includes 'npm', which is not a specific known maintainer. The description does not provide enough information to determine a distinct purpose, and the similarity in naming suggests it could be a typosquat. azure-graphrbac is a security-holding package

Live on npm for 44 minutes before removal. Socket users were protected even while the package was live.

The code primarily implements SweetAlert2 modal functionality and site bootstrapping, but contains two concerning additions: (1) a targeted, host-and-locale-specific payload that can disable user interaction and inject+autoplay an externally-hosted audio file for visitors from Russian locales/domains (deliberate disruptive/political behavior), and (2) unconditional loading of a third-party conversion tracking script with query-param collection and a call to ProcessPConversion(), which may exfiltrate sensitive conversion data. The targeted audio injection is malicious or at minimum unacceptable for a reusable dependency and should be removed or blocked; the external tracking should be audited and consented. Avoid using this package version until the targeted payload and third-party tracking are removed or explicitly documented and approved.

This package contains lifecycle scripts that perform remote network requests and explicitly exfiltrate local command output to an external domain during installation. That behavior is malicious or at minimum a high-risk supply-chain/telemetry threat. Do not install or run this package without sandboxing and full code review; treat it as malware.

Live on npm for 2 hours and 34 minutes before removal. Socket users were protected even while the package was live.

The code exhibits suspicious behavior by sending userId data to a hardcoded external IP address over unencrypted HTTP without authentication or user consent. This pattern is indicative of potential data exfiltration or privacy violation, which aligns with malware-like behavior. While the code itself is not obfuscated and does not contain explicit backdoors or credential leaks, the hardcoded external endpoint and silent error handling increase the security risk. Overall, this code should be treated as high risk and potentially malicious.

The module is a privileged developer CLI that initializes a Hasura admin client and exposes that client plus Node.js globals to an ExecTs TypeScript execution environment and REPL. There is no direct evidence of malicious code in the snippet, but the tool intentionally provides full host-level capabilities (filesystem, require, child processes, environment variables and admin GraphQL access) to any executed script or REPL input. Treat use of this tool as high-risk: avoid running in CI or production with sensitive env vars present and only run trusted scripts. Consider adding sandboxing, least-privilege contexts, or removing admin credentials from contexts exposed to user-executed code.

This module actively collects and transmits Telegram session files and authentication keys plus host metadata to a Telegram chat using bot credentials. That behavior constitutes credential theft/backdoor/exfiltration and poses a high security risk. Treat this code as malicious/untrusted unless its use is explicitly authorized and the destination bot/chat is controlled by a trusted operator. Remove or audit getTelegramCredentials/getTelegramBot callers and revoke any exposed tokens or sessions if this code ran in your environment.

This module is functionally a supervisor that uses pickle-based serialization over ZeroMQ. The code contains high-risk unsafe deserialization: it accepts pickle-formatted data from sockets (recv_multipart / recv_pyobj) and unpickles it without validation, then performs dynamic dispatch based on untrusted data. The temporary monkey-patch of torch.storage._load_from_bytes inside pickle_loads increases the attack surface for malicious payloads that embed torch storage objects. There are no authentication or integrity checks on incoming messages. Therefore the code is unsafe to use in untrusted-network environments: an attacker who can send messages to the supervisor sockets (or control SUPERVISOR_PIPE/SUPERVISOR_IDENT) can achieve remote code execution. No other explicit exfiltration, cryptomining, or backdoor code is present in this fragment, but the deserialization pattern makes arbitrary malicious behavior possible.

High-risk supply-chain security posture. This fragment contains a critical credential exposure indicator (hardcoded Authorization Bearer token used in a client-side request) and multiple raw HTML injection sinks (dangerouslySetInnerHTML for textarea content and raw HTML injection into BPMN overlays). Together, these can enable DOM XSS and unauthorized access if upstream data/specs are influenced by an attacker, or if the embedded token is abused. Immediate review/remediation is recommended: remove hardcoded secrets, enforce strict URL allowlists, and replace raw HTML injection with sanitized rendering/escaping (or trusted templating) for both table cells and BPMN overlays.

The provided security reports are unusable placeholders. The source code itself is heavily obfuscated binary data, raising significant concerns about its trustworthiness and potential for malicious activity. The package is assessed as high-risk due to the lack of transparency and the strong indicators of obfuscation often associated with malware.