42Crunch vs AIShield

About AIShield

AIShield provides security for AI/ML models and GenAI applications, addressing vulnerabilities like prompt injections, jailbreaks and data leaks. AIShield is a full-stack security product, based on technical research over four years and over 45 patents, that defends AI-based application workloads across on-prem, cloud and edge environments. AISpectra is designed to keep AI/ML models and LLM applications secure throughout development. AISpectra covers AI models and LLM applications at every stage, from development to testing and training. AIShield Guardian is designed to provide real-time security to live AI/ML and Generative AI applications.^{[2][3][4][6][8][10]}

AIShield states that traditional security measures fail to address AI-specific risks like adversarial attacks and data leakage. AIShield states that after deployment, the lack of an AI Firewall and real-time monitoring leaves AI models and LLM applications vulnerable to threats including prompt injection and data leakages. Guardian offers protection for deployments of LLM-powered chatbots, algorithmic trading models and AI-driven automation systems.^[4]

AISpectra automates model and notebook discovery and performs vulnerability assessments for AI supply chain security. AISpectra is an AI model scanner that provides discovery and vulnerability assessment for AI systems. AISpectra scans repositories to identify models, notebooks and artifacts. AISpectra protects against embedded malicious code, outdated or unsafe libraries and PIIs. AISpectra identifies issues such as hardcoded secrets, model serialization attacks and unsafe operations. AISpectra offers customizable scanning policies to align with organizational security standards. AISpectra tracks repository changes for version control. AISpectra supports third-party and proprietary models. AISpectra generates reports tied to industry benchmarks like OWASP and MITRE ATLAS.^[1][2][4][6]

AISpectra performs automated red teaming for ML, uncovering vulnerabilities like adversarial attacks, model theft and data poisoning. AISpectra uses real-time simulations and detailed reports to secure AI assets throughout the ML development lifecycle. AISpectra maps AI models, pipelines and artifacts. AISpectra detects risks like model theft, evasion attacks and inference vulnerabilities. AISpectra applies automated red teaming to LLM security, uncovering vulnerabilities like prompt injections and jailbreaks. AISpectra employs static and dynamic queries, including human-crafted prompts, to uncover vulnerabilities. AISpectra uses a library of over 50,000 attack scenarios. AISpectra covers adversarial and non-adversarial scenarios, from prompt injections to data leakage. AISpectra assigns a threat posture score, categorizes vulnerabilities by severity and provides recommendations. AISpectra ties vulnerabilities to frameworks like MITRE ATLAS, OWASP and the EU AI Act.^{[1][2][4][7][8]}

AISpectra is offered as SaaS, in the customer cloud or on-premises, with features like SSO and data retention. AISpectra works on AIShield Cloud (SaaS), on customer cloud instances or in on-premise environments. AISpectra integrates with a cloud-based UI, API and CI/CD pipelines and produces customizable reports in JSON or SARIF format. AISpectra provides dashboards that categorize attacks by severity and give actionable steps. AISpectra supports OWASP, MITRE ATLAS, the EU AI Act and NIST guidelines for regulatory standards.^[4][7]

AIShield is available on the AWS and Azure marketplaces. AIShield vulnerability scanning covers attacks such as theft, poisoning, evasion and inference for computer vision, tabular classification and time-series forecasting models, with APIs and dashboards. AIShield supports 200+ attack types across 20+ types of models and data type variations. AIShield provides an SDK and APIs that integrate into ML workflows such as AWS Sagemaker and Azure ML. AIShield integrates with monitoring platforms like WhyLabs and confidential computing platforms like Fortanix. AIShield sends attack telemetry to SIEM/SOAR tools like Splunk and Microsoft Sentinel through preconfigured connectors. AIShield provides reference implementations with a python SDK.^[3]

Guardian ML Firewall detects and mitigates adversarial threats like extraction, evasion and poisoning against Machine Learning applications. Guardian provides runtime security for Machine Learning (ML) applications and acts as a firewall against adversarial threats. Guardian ML Firewall generates threat-informed defenses and simulates attacks. Guardian ML Firewall monitors for threats in real time and mitigates risks automatically without interrupting workflows. Guardian ML Firewall keeps input-output data pipelines untampered by blocking malicious manipulations. Guardian ML Firewall integrates with Splunk, IBM QRadar, MS Sentinel and Amazon Security Lake for centralized monitoring and threat hunting. Guardian provides continuous security for ML deployments across cloud and edge environments.^[1][2][9]

Guardian provides security for Generative AI (GenAI) applications and LLMs, mitigating risks like prompt injection attacks, jailbreaks and sensitive data exposure. Guardian safeguards AI inputs and outputs with customizable content controls, including bias detection and PII anonymization. Guardian supports 75+ configurable policies, including topic filtering and compliance with PII regulations. Guardian blocks prompt injection, detects invisible text and redacts sensitive information dynamically. Guardian blocks toxic language, competitor mentions and sensitive information. Guardian configures and enforces role-specific access controls and content guidelines. Guardian tracks API interactions, identifying and mitigating risks as they occur. Guardian operates in Audit Mode (Out-of-Band), for monitoring without affecting traffic flow to the target LLM, and in Block Mode (In-Sync), for real-time protection with traffic orchestration. Guardian covers text and image-based inputs and outputs. Guardian integrates with orchestration frameworks like CrewAI, Phidata and Microsoft Autogen for AI-driven workflows. Guardian connects with SIEM tools like Splunk, IBM QRadar and Microsoft Sentinel. Guardian supports cloud, hybrid and on-premises deployments, including SaaS and Bring Your Own Cloud (Docker, Kubernetes). Guardian receives automatic updates for SaaS deployments and monthly updates for self-hosted environments, with disaster recovery support and configurable RTO and RPO.^{[1][3][6][7][9][10]}