Lacework, Sweet Security, Sysdig and Upwind

About Sweet Security

Sweet Security agents learn how each application, agent and workload should behave. Sweet Security blocks a rogue agent the moment it acts and traces the full attack path from prompt to data.^[2]

Sweet Security combines Cloud Detection and Response (CDR), Application Detection and Response (ADR) and Cloud Workload Protection (CWPP) to detect attacks across modern cloud environments. Sweet Security unifies data from eBPF sensors and cloud logs to create a behavioral baseline of each environment. Sweet Security uses an eBPF-based sensor that performs application profiling. Sweet Security scores incidents and states what requires immediate attention. Sweet Security lets teams terminate malicious processes, manually or automatically, without disrupting the production environment.^[2][3][4]

Sweet Security gives SOC and Incident Response teams a complete picture of incidents across the cloud, workload, and application layers. Sweet Security captures processes, file accesses, network traffic and memory usage. Sweet Security tags events using the MITRE ATT&CK framework. Sweet Security correlates signals from every layer into a single incident. Sweet Security sends alerts via Slack, Jira, ServiceNow or custom webhooks. Sweet Security integrates with SOAR tools like Torq to automate full incident containment. Sweet Security lets teams build custom detections using signals from cloud logs, workload data, or L7.^[4]

Sweet Security shows runtime communication of cloud assets, both internally and externally. Sweet Security keeps an up-to-date overview of clusters, networks, databases, secrets and operating systems. Sweet Security identifies connections to external entities, unauthorized ports and connections to malicious DNSs or IPs. Sweet Security discovers human and non-human identities such as service accounts, IAM users, API keys and tokens. Sweet Security detects identity-based anomalies such as unauthorized access attempts, unusual privilege escalations and irregular usage patterns. Sweet Security detects secrets stored in plaintext or exposed in environment variables. Sweet Security integrates with identity providers (OIDC).^[5][6][9]

Sweet Security evaluates the risk and business impact of each vulnerability by combining LLMs with real-time runtime context. Sweet Security prioritizes vulnerabilities based on real-world exploitability indicators. Sweet Security builds a runtime-powered SBOM. Sweet Security detects misconfigurations in real time, not just through periodic scans. Sweet Security runs ongoing compliance checks across frameworks including HIPAA, CIS Kubernetes Benchmark, GDPR, NIST and SOC2. Sweet Security gives a unified view of toxic combinations by cross-correlating misconfigurations, exposed assets, executed vulnerabilities and over-permissive access.^[7][8]

Sweet Security uses Layer 7 visibility to understand API behavior, detect malicious activity and stop application-layer threats before they escalate. Sweet Security organizes APIs by individual endpoints to track request methods, error rates and potential vulnerabilities. Sweet Security identifies misconfigurations, exposed APIs and outdated dependencies across an API ecosystem. Sweet Security monitors first- and third-party application behavior at runtime to detect anomalies, unauthorized activity and signs of active exploitation. Sweet Security analyzes application behavior at the package and function level. Sweet Security can automatically block malicious activity in real time. Sweet Security filters attack attempts by threat type, such as SQLi, XSS and SSRF, and by status code.^[9][10]

Sweet Security continuously monitors AI infrastructure, including agents, models and APIs, to detect and neutralize risks as they emerge. Sweet Security automatically discovers AI services through API (L7) analysis and builds a real-time inventory of AI agents and their data flows. Sweet Security identifies unsanctioned AI tools and models operating outside IT and security oversight, such as rogue APIs or unmanaged ML models. Sweet Security detects sensitive data in prompts, unauthenticated or unencrypted AI access, and other policy violations. Sweet Security monitors for Personally Identifiable Information (PII), secrets and other sensitive data traversing AI workflows. Sweet Security identifies hidden or unauthorized APIs that may expose sensitive data.^[11]

Sweet Security gives AppSec teams continuous visibility into how applications behave, including what APIs are exposed, which vulnerabilities are exploitable, where sensitive data flows and where attackers are actively probing. Sweet Security unites security and development teams around shared runtime context. Sweet Security offers SOC, IR, DevSecOps and AppSec teams integrations across SIEMs, SOARs, alerting and ticketing systems.^{[3][7][8][10][12][13]}

About Sysdig

Sysdig delivers real-time defense for cloud, containers, and AI agents. Sysdig captures live system calls at the kernel level, which shows what is actually running in the cloud.^[3]

Sysdig offers an agentless approach that provides visibility into cloud security posture, covering vulnerabilities, misconfigurations, in-use permissions, and threats. Sysdig delivers real-time threat detection across workloads, identities, cloud services, and third-party apps by combining drift control, machine learning, and Falco rules curated by the Sysdig Threat Research Team. Cloud Attack Graph correlates assets, activity, and risks across domains to uncover hidden attack paths and accelerate incident detection and response. Sysdig combines runtime insights, such as in-use vulnerabilities and in-use permissions, with static assessments, including misconfigurations and known security flaws, to generate a prioritized list of the riskiest findings.^[1][5][6]

Sysdig uses a graph model that continuously ingests and correlates data from cloud APIs, configurations, identity permissions, and runtime insights. Sysdig maintains an inventory of cloud resources, enriched with compliance violations, vulnerabilities, and IAM misconfigurations. For workloads, Sysdig detects workload and container threats in real time with out-of-the-box detection rules, powered by Falco and curated by the Threat Research Team. For vulnerabilities, Sysdig prioritizes vulnerabilities tied to in-use packages, enriched with context like exploitability, exposure, and asset criticality. CVE360 offers a complete picture of each vulnerability, including its source, affected resources, and how to fix it. Sysdig identifies high-impact fixes at the source, such as a patch to a base image that resolves dozens of downstream vulnerabilities. Sysdig Sage provides AI-powered remediation guidance with step-by-step instructions in natural language.^[6][7][8]

Sysdig delivers real-time detection across Linux and Windows servers, containers and Kubernetes, cloud logs and trails, and Serverless (FaaS). Sysdig correlates identity activity patterns with workload exploits to detect compromised identities and stop attacks at the first sign of privilege escalation and account compromise. Sysdig server threat detection starts with a lightweight agent, fueled by the Falco detection engine. The Sysdig agent streams kernel-level events, cloud service logs, and Kubernetes metadata in real time. For infrastructure as code, Sysdig automatically scans infrastructure code during development to detect misconfigurations, policy violations, and vulnerabilities in Terraform, CloudFormation, Kubernetes manifests, and other IaC templates before they reach production. Sysdig enforces security standards directly in the development workflow using OPA-based policies.^[9][10][11]

The Sysdig GenAI Assistant, formerly Sysdig Sage, is powered by an autonomous agents architecture and employs multi-step reasoning and contextual awareness. The Sysdig GenAI Assistant can respond to user queries on cloud detection and response, posture management, and vulnerability management. The Sysdig GenAI Assistant is available as a conversational assistant and embedded directly into the UI. Secure AI extends the Sysdig Secure platform with an expert AI security team. Secure AI can run inside the agents a team already uses, take on the work, or answer questions along the way. Sysdig connects its platform to the AI agents a team already uses through curated agent skills and an MCP server. Sysdig Secure lets users define desired outcomes while autonomous agents handle the work.^[3][12]

Sysdig Monitor provides visibility into Kubernetes clusters, namespaces, workloads, pods, and containers, regardless of cloud platform. Sysdig Monitor collects metrics about an environment, then correlates and enriches those metrics. Sysdig grew out of open source and supports open standards. The Sysdig Threat Research Team monitors emerging attacker behaviors and cloud-native threats and turns real-world insights into actionable detections. Sysdig's Threat Research Team has spent years uncovering novel cloud attacks, from JADEPUFFER to SCARLETEEL.^{[1][3][13][14]}

Sysdig describes a product for defending Kubernetes, containers, and hosts in on-premises, air-gapped, and private cloud environments. Sysdig cloud detection and response is designed to provide advanced capabilities across multi-cloud, hybrid, and on-premises infrastructures. The security and engineering teams at BigCommerce use Sysdig to identify and eliminate misconfigurations and streamline compliance. Neo4j needed a cloud security platform that provided unified coverage across its cloud environment. Apree Health uses Sysdig for security and incident response and for visibility into its Kubernetes deployment.^{[3][5][6][7][8][10][11]}

About Upwind

Upwind sells security for cloud workloads, APIs and agents, combining their context with runtime intelligence to identify critical risks and catch new attacks in real time. Upwind describes itself as a runtime security platform that enables security professionals to navigate toward the root cause of security issues. Upwind states a mission to give security teams and AI agents what they need to remediate risks and respond to threats as they occur. Security teams use Upwind to detect, prioritize and respond to real risks. Upwind was founded by the team behind Spot.io, a cloud infrastructure optimization company acquired by NetApp.^{[1][3][5][8][9]}

Upwind provides a live map of the environment showing which workloads and agents are running, who owns them, what they communicate with and what data they can reach. Upwind connects workload runtime signals and cloud activities to spot deviations in cloud and AI activity as they occur. Upwind offers specialized AI agents that investigate threats, provide red team validation and offer remediation. By combining runtime intelligence with cloud workload, API and agent context, Upwind focuses teams on critical risks, reachable exposures, remediation and real-time threat detection.^[1][3]

For cloud posture, Upwind inventories all cloud resources, services and technologies across environments. Upwind maps assets, attributes, ownership and relationships into a single view. Upwind analyzes how risks relate and propagate across interconnected assets. Upwind pushes prioritized findings into CI/CD, alerting, chat and ticketing systems.^[6]

Upwind's Agentic Pack combines runtime-powered security context with specialized AI agents that investigate, validate and drive remediation across the environment. Choppy unifies Upwind's security context, specialized AI agents and workflows into one conversational control plane. Red safely tests the environment the way an adversary would, proving which risks are reachable in production. Upwind analyzes an entire finding set together to find the few hotspots where a single change fixes thousands of issues at once. Green surfaces the handful of changes that eliminate the most risk, ranked by what they remove. Upwind delivers implementation-ready changes across code, IaC, packages, images and cloud configuration as Pull Requests.^[1][7]

Upwind scans every layer of cloud infrastructure to secure AI applications from code to runtime. Upwind states that users can see a complete AI inventory, improve AI posture and respond to AI threats in realtime. Upwind maps all AI resources in cloud providers, AI platforms, active workloads and endpoint devices. Upwind discovers unsanctioned models, tools and third-party AI services adopted outside approved governance. Upwind produces a full bill of materials for the models, datasets, packages and dependencies behind every AI application. Upwind shows which sensitive data AI systems can reach and which identities and permissions they inherit. Upwind inspects agents, their tools, MCP connections and instructions for risky configurations and prompt injection paths. Upwind assesses AI configurations continuously against benchmarks and regulatory frameworks. Upwind monitors the AI stack for prompt injection, data exfiltration and agent misuse. Upwind runs continuous offensive testing for every model, agent and MCP server that an organization exposes.^[8][9]

Upwind auto-discovers managed, unmanaged and shadow APIs across clouds and containers. Upwind protects REST, GraphQL, gRPC, SOAP and legacy protocols with unified controls. Upwind identifies PII, PHI, PCI and secrets flowing through APIs. Upwind spots abuse patterns such as brute force, lateral movement and token misuse.^[9]

Upwind's secret scanning detects and blocks API keys, tokens and hardcoded passwords. Upwind analyzes configuration files like Terraform and CloudFormation for critical security flaws before they are deployed. Upwind's Admission Controller enforces granular policies to stop insecure workloads from starting. Upwind prevents privileged containers, root access and unverified images from running. Upwind validates image signatures and verifies provenance at the door, so that the container trying to run is the artifact the team built and verified. Upwind correlates build-time alerts with live runtime data to show which vulnerable packages are loaded, running and exploitable. When a runtime threat is detected, Upwind traces it back through the build pipeline to identify the specific repo, commit and developer owner.^{[1][3][5][7][10]}