LLakera focuses on AI security by providing threat intelligence for GenAI applications. Its flagship product, Lakera Guard, shields large language models and GenAI apps from risks such as prompt injections, data leakage, and other content hazards. The product works through a proprietary threat intelligence database that aggregates insights from LLM deployments, Gandalf, open-source data, and dedicated ML research, and is exposed to users via an API that can be integrated with one line of code. Lakera targets organizations of all sizes and offers cloud or on-premises deployment, with an enterprise-facing pricing model and a free trial. A key differentiator is its large, continuously growing threat database—tens of millions of attack data points, expanding by over 100,000 entries daily—that improves defenses over time. Overall, Lakera aims to help organizations deploy AI applications securely and at scale by providing enterprise-grade protection for AI deployments.
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Company Stage
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Total Funding
$30M
Headquarters
Zurich, Switzerland
Founded
2021
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HiddenLayer raises $100 million in Series B funding round. HiddenLayer's $100 million Series B positions the Austin-based AI security company as a leading pure play provider securing agentic, generative, and predictive AI systems amid surging enterprise demand. HiddenLayer's recent $100M round was led by Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, M12 (Microsoft's venture fund), and Booz Allen Ventures. This brings HiddenLayer's total capital raised to approximately $156 million. Prior rounds included a roughly $6 million seed in 2022 and a $50 million Series A in September 2023 (co-led by M12 and Moore Strategic Ventures). Secondary market data places a post money valuation in the range of roughly $383-387 million. The company, founded in 2022 by Chris "Tito" Sestito (CEO) and co-founders including security and AI veterans, employs around 175 people. How will HiddenLayer use the funds? Funds will deepen the enterprise platform with emphasis on Agentic Runtime Security (real time visibility into agent behavior in production, detecting and blocking manipulation, tool misuse, and unauthorized actions) and the new Agent Harness Security solution, which extends runtime protection to autonomous coding agents that write, review, and ship code with reduced human oversight. Additional priorities include sales and distribution expansion, engineering and research growth, channel relationships, leadership hires (including recent Chief Revenue Officer Mike Gesnaldo), and international expansion starting in Europe and the broader EMEA region. Annual recurring revenue (ARR) grew more than 10x over the past year and now sits in the "tens of millions" of dollars, with over 90% of that growth driven by new customers. The company added more than 50 new platform customers across securities brokerage, banking, insurance, accounting, government, technology, IT services, pharmaceuticals, and airlines. International wins include one of the world's largest pharmaceutical companies plus premium automotive and food and beverage brands. It also supports a leading frontier model provider securing systems used by more than 700 million weekly users. HiddenLayer's platform covers the full AI lifecycle: discovery and inventory of AI assets, supply chain and model scanning (detecting risks in third party and proprietary models without requiring access to raw training data or model weights), red teaming/attack simulation, guardrails, and runtime protection including an AI firewall. A key differentiator is its non invasive approach that works without accessing sensitive data or proprietary model internals, valuable for regulated industries and federal customers. Research underpins the product: 39 granted patents and 65 pending spanning adversarial detection, model protection, and threat analysis; development of the first comprehensive Adversarial Prompt Engineering taxonomy; and ongoing vulnerability disclosures across foundation models, agents, and supporting tools. The team contributes to CISA/JCDC, MITRE, NIST, OWASP, and OpenSSF. Its 2026 AI Threat Landscape Report notes that while 96% of organizations view AI as critical to operations, nearly one third cannot confirm whether they have experienced an AI related breach. Gartner estimates enterprise spending on products to secure AI tools will reach $2.83 billion in 2026 (up 83% from 2025) and nearly $4.78 billion the following year. The round ranks in the 96th percentile of U.S. Series B deals in the AI security space. HiddenLayer competes in a rapidly consolidating category against specialists and broader platforms such as Protect AI, Lakera, Robust Intelligence (now under Cisco), and others focused on model security, runtime guardrails, or supply chain integrity. Large cybersecurity incumbents (Cisco, Palo Alto Networks, Check Point) often prefer to acquire rather than build native AI security capabilities. The syndicate blends growth equity (Delta-v), cybersecurity specialists (Ten Eleven), strategic corporate capital (M12, Booz Allen Ventures), and institutional finance (Morgan Stanley). Microsoft's continued participation signals alignment with enterprise AI platforms. Investor commentary highlights the shift from design time principles to continuous runtime assurance as agentic systems become core to enterprise operations, and notes that traditional tools built for code and infrastructure are insufficient against model poisoning, hijacking, or input based manipulation. The raise capitalizes on proven product market fit in high stakes verticals, strong research IP, and the accelerating transition to agentic AI, providing runway to scale sales, product depth in runtime agent protection, and geographic reach while the AI security category matures into a multi billion dollar market. Please email Daily Company your feedback and news tips at hello(at)dailycompanynews.com
NVIDIA goes open source with a big batch of physical AI agent tools. 2026-06-01 11:06 Read the original article: NVIDIA and Lakera AI have introduced a groundbreaking unified security and safety framework designed to address the emerging challenges posed by autonomous AI agents in enterprise environments. This collaborative effort represents a significant step forward in making agentic systems AI systems capable of independent planning, tool use, and multi-step task... December 8, 2025 Enterprises are rushing to deploy agentic systems that plan, use tools, and make decisions with less human guidance than earlier AI models. This new class of systems also brings new kinds of risk that appear in the interactions between models, tools, data sources, and memory stores. A research team from... December 8, 2025 June 7, 2024 In "CySecurity News - Latest Information Security and Hacking Incidents"
AISI and Lakera open source 'b3' to strengthen AI agent security. Open-source software The UK AI Security Institute, in collaboration with Check Point and Lakera, has unveiled an open source benchmark 'b3' to strengthen LLM security for AI agents. The UK AI Security Institute (AISI) has partnered with Check Point and its subsidiary Lakera to launch the Backbone Breaker Benchmark (b3), an open source framework designed to enhance the security and resilience of large language models (LLMs) that power AI agents. Built to make LLM security measurable and transparent, b3 focuses on identifying the specific "pressure points" where LLMs fail - such as when prompts, files, or web inputs trigger malicious outputs. Rather than evaluating full agent workflows, the benchmark isolates the individual steps most vulnerable to attack.
Lakera launches open-source security benchmark for LLM backends in AI agents. Check Point Software Technologies Ltd. and Lakera, a leading AI-native security platform for Agentic AI applications, with researchers from The UK AI Security Institute (AISI), today announced the release of the backbone breaker benchmark (b3), an open-source security evaluation designed specifically for the security of the LLM within AI agents. The b3 is built around a new idea called threat snapshots. Instead of simulating an entire AI agent from start to finish, threat snapshots zoom in on the critical points where vulnerabilities in large language models are most likely to appear. By testing models at these exact moments, developers and model providers can see how well their systems stand up to more realistic adversarial challenges without the complexity and overhead of modelling a full agent workflow. "We built the b3 benchmark because today's AI agents are only as secure as the LLMs that power them," said Mateo Rojas-Carulla, Co-Founder and Chief Scientist at Lakera, a Check Point company. "Threat Snapshots allow us to systematically surface vulnerabilities that have until now remained hidden in complex agent workflows. By making this benchmark open to the world, we hope to equip developers and model providers with a realistic way to measure, and improve, their security posture." The benchmark combines 10 representative agent "threat snapshots" with a high-quality dataset of 19,433 crowdsourced adversarial attacks collected via the gamified red teaming game, Gandalf: Agent Breaker. It evaluates susceptibility to attacks such as system prompt exfiltration, phishing link insertion, malicious code injection, denial-of-service, and unauthorized tool calls. Initial results from testing 31 popular LLMs reveal several key insights: * Enhanced reasoning capabilities significantly improve security. * Model size does not correlate with security performance. * Closed-source models generally outperform open-weight models - though top open models are narrowing the gap. Gandalf: Agent Breaker is a hacking simulator game that challenges you to break and exploit AI agents in realistic scenarios and the ten GenAI applications inside the game simulate how a real-world AI agent behaves. Each application features multiple difficulty levels, layered defenses, and novel attack surfaces designed to challenge a range of skill sets, from prompt engineering to red teaming. Some of the apps are chat-based, while others rely on code-level thinking, file processing, memory, or external tool usage. The initial version of Gandalf was born out of an internal hackathon at Lakera, where blue and red teams tried to build the strongest defenses and attacks for an LLM holding a secret password. Since its release in 2023 it has become the world's largest red teaming community, generating more than 80 million data points. Initially created as a fun game, Gandalf exposes the real-world vulnerabilities in GenAI applications to raise awareness about the importance of AI-first security.
Check Point has acquired AI security firm Lakera.AI for an estimated $300 million. This acquisition enhances Check Point's AI security capabilities, offering a comprehensive AI security stack for enterprises. Lakera, founded in 2021, specializes in securing AI environments with products like Lakera Red and Lakera Guard. The company also developed Gandalf, a major AI security testing platform. Lakera operates R&D centers in Zurich and San Francisco, employing about 70 people.
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Industries
Company Size
51-200
Company Stage
Acquired
Total Funding
$30M
Headquarters
Zurich, Switzerland
Founded
2021
Find jobs on Simplify and start your career today
We update Lakera's jobs every few hours, so check again soon!Browse all jobs