For AI Builders & Trainers
Train And Deploy AI Without Compromising Speed Or Safety
Detect poisoned training data and shadow prompts embedded in code, documents, and datasets before they change model behavior.
Secure AI Without Breaking The Pipeline
As models grow in size, capability, and exposure, security must keep pace.
PromptShield™ protects AI systems at scale without retraining models or re-architecting your stack.
Model integrity stays intact
Runtime protection preserves training speed, evaluation accuracy, and model performance.
Intent becomes visible
AI misuse and prompt-based attacks are detected beyond what test cases can reveal.
Security scales without rework
Guardrails extend from experimentation to production without retraining models or rebuilding pipelines.
AI Protection Built For Training & Deployment
Modern AI teams need security that keeps pace with experimentation and scale.
PromptShield™ protects models at runtime—preserving training speed, evaluation integrity, and deployment velocity.
PromptShield™ Secures Training Pipelines Against Data Poisoning, Leakage, And
Hidden Prompt Attacks Introduced Through Datasets, Files, Or Tooling
Prevents poisoned training data from altering model behavior.
Detects shadow prompts hidden in code, notebooks, datasets, and documents.
Stops leakage of sensitive data during training and evaluation.
Protects fine-tuning, RAG ingestion, and evaluation workflows
PromptShield™ Deployment Options
From edge to core, PromptShield™ adapts to your architecture: cloud, on-prem, or hybrid with scalable inspection depth.
L1 Presence Detection plug & play / no risk | L2 Full Detection plug & play / very low risk | L3 Inline Blocking redundancy required | |
PromptShield™ AI Firewall & Intent Engine included in every deployment | ✓ Active Intelligence and dashboards | + 2 way threat detection and logging + Collects risk data compiled but no traffic blocked | + Blocks malicious prompts in real time + Rewrites unsafe responses + Enforces policy decisions in-path |
On Premises / Virtual Machine | ✓ IDS Node, virtual or plug and play device ✓ Set-up with ongoing support | + PromptShield™ attached to firewall handling only AI domains | + Enterprise level rack mount |
Cloud | ✓ AWS/Cloud deployment ✓ VM machine & Container | + AI domains steered entirely for PromptShield™ handling | + Secure AI Gateway for complete AI traffic flow control + High performance VM/full load balancing |
Full Stack AI Security Without The Complexity
PromptShield™ unifies runtime inspection, intent-aware detection, and pipeline-safe guardrails
—so AI teams can protect models from training through production without redesigning workflows.
PromptShield™ In Practice
Each short video highlights a real scenario: a risk appears, PromptShield™ intervenes, and teams stay productive without disruption.
Simple, fast, and built for real environments.
PromptShield™ Vs LLMs Exploiting NPM Packages
PromptShield™ Vs Claude File Creation Attacks
The Hidden Risks Of AI Data Poisoning
Frequently Asked Questions
Explore how PromptShield™ helps teams use AI every day—while keeping models, workflows, and code protected.
What Are The Primary Security Risks Associated With Building And Training AI Applications?
A significant concern is adversarial AI attacks, where malicious actors manipulate AI models by introducing subtle perturbations to input data, leading to incorrect outputs. Another risk is the presence of poisoned training data, where attackers inject misleading or harmful data into the training set, causing the model to learn and propagate incorrect patterns.
Implementing robust cybersecurity strategies, such as regular audits, employee training, and the use of tools like PromptShield™, can help mitigate these risks.
How Can Organizations Detect And Prevent Poisoned Training Data In AI Models?
Detecting and preventing poisoned training data is crucial for maintaining the integrity of AI models. Organizations should implement data validation techniques to identify and filter out anomalous or suspicious data points before they are used in training. Additionally, employing robust machine learning algorithms that are less sensitive to outliers can reduce the impact of poisoned data.
Establishing clear data governance policies and conducting thorough audits of data sources can further prevent the introduction of malicious data. Utilizing tools like PromptShield™ can also provide an additional layer of protection against adversarial inputs.
What Strategies Can Organizations Employ To Secure AI Applications During Development And Deployment?
To secure AI applications, organizations should adopt a comprehensive cybersecurity strategy that includes several key components. First, conducting regular risk assessments to identify potential vulnerabilities in AI systems is essential. Implementing a defense-in-depth approach, which layers multiple security measures, can provide robust protection against various threats. Establishing a zero-trust security model ensures that all users and devices are continuously authenticated and authorized.
Additionally, integrating AI security into the organization’s overall cybersecurity framework and providing ongoing employee training on AI-related risks can enhance the security posture of AI applications.
How Does PromptShield™ Enhance The Security Of AI Applications?
PromptShield™ is an intent-based AI prompt web application firewall designed to protect enterprises from critical AI security risks. It monitors and filters AI prompts to prevent adversarial inputs, such as prompt injections, from compromising AI models.
By analyzing the intent behind prompts, PromptShield™ can detect and block malicious attempts to manipulate AI behavior, ensuring that AI applications operate as intended.