Multi cloud and AI era

Today's Challenges

Hybrid Cloud

Artificial Intelligence

Complexity in management detracts from cost benefits.
Ensuring compliance with data protection regulations is challenging.
Integrating legacy apps with cloud and SaaS can cause compatibility issues.
Expanding the attack surface increases exposure to threats.

Artificial Intelligence

Requires centralizing huge amounts of sensitive data.
Threat actors can exploit weaknesses in AI models to break out of guardrails.
Rate of adoption is outstripping efforts to do so responsibly.
Training data can be unintentionally exposed to users.

Solution: Centralized data security and compliance

Discover

Analyze & Respond

Discover

Automate discovery and classification of on premises and cloud data and uncover critical vulnerabilities

Encrypt

Analyze & Respond

Discover

Safeguard privacy and confidentiality of data at rest, in motion, and in use with encryption and key management

Monitor

Analyze & Respond

Protect and harden on-prem and cloud data sources, including Azure Event Hubs, AWS Kinesis, Snowflake, SAP, etc.

Analyze & Respond

Identify and respond to compliance and data security risks, across environments and teams, from one place,

& generate reports and automate notification.

1. Protect sensitive data

3. Keys or tokens found in Slack

1. Protect sensitive data

Prevent usage of sensitive information in AI model found in big data (ex. Parquet) and meet compliance.

2. Unintentional exposure

3. Keys or tokens found in Slack

1. Protect sensitive data

Monitor copies of sensitive data across apps and clouds to prevent exposure to a 3rd party (ex. unapproved open source models)

3. Keys or tokens found in Slack

Detect if keys are exposed in shared slack channels, which can give access to attackers who aim to steal IP

4. Prevent data leakage

5. Data Transfer Violation

3. Keys or tokens found in Slack

Detect if sensitive data (ex. PII) has leaked during model validation (could be from insider threat)

5. Data Transfer Violation

Monitor data flow to ensure compliance across SaaS applications in various geographies (ex. GDPR

Security for the hybrid cloud and AI era

Today's Challenges

Hybrid Cloud

Artificial Intelligence

Artificial Intelligence

Artificial Intelligence

Artificial Intelligence

Artificial Intelligence

82% of data breaches involved data stored in cloud environments.

82% of data breaches involved data stored in cloud environments.

82% of data breaches involved data stored in cloud environments.

24% of current AI projects are being secured.

82% of data breaches involved data stored in cloud environments.

82% of data breaches involved data stored in cloud environments.

Solution: Centralized data security and compliance

Discover

Analyze & Respond

Discover

Encrypt

Analyze & Respond

Discover

Monitor

Analyze & Respond

Analyze & Respond

Analyze & Respond

Analyze & Respond

Analyze & Respond

Secure the AI pipeline with Guardium

1. Protect sensitive data

3. Keys or tokens found in Slack

1. Protect sensitive data

2. Unintentional exposure

3. Keys or tokens found in Slack

1. Protect sensitive data

3. Keys or tokens found in Slack

3. Keys or tokens found in Slack

3. Keys or tokens found in Slack

4. Prevent data leakage

5. Data Transfer Violation

3. Keys or tokens found in Slack

5. Data Transfer Violation

5. Data Transfer Violation

5. Data Transfer Violation

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