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Based on our record, GitHub seems to be a lot more popular than Strac.io. While we know about 2472 links to GitHub, we've tracked only 7 mentions of Strac.io. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Strac | https://strac.io | Remote US | Senior Software Engineering About Strac: * We're a ~5-person team (Seattle, and remote US) with a mission to discover and remediate sensitive data across SaaS, Cloud apps and Endpoint devices. * We protect hundreds of enterprises with our unique data discovery and data loss prevention (dlp) solution * Our backend detects sensitive data... - Source: Hacker News / about 2 years ago
Hi u/nyhr666, At Strac, we have built a DLP (Data Loss Prevention) solution that prevents files in Google Drive to be shared with external users. It is highly workflow driven where if anyone wants to share, the owner will get an alert whether to approve or decline the request. If approved, file will be shared; else blocked. Source: over 3 years ago
Today, Strac launched Google Sheet Redactor on Product Hunt. Source: over 3 years ago
Hi u/alljoysun, We at Strac are a DLP (Data Loss Prevention) company. We protect businesses from sensitive data risks that arise from using AWS services. Happy to chat. Source: over 3 years ago
Disclaimer: We built Strac to exactly solve your problem of not having to worry about sensitive data (PII, PCI and PHI). We are 100% native on AWS. You can get our entire secure infrastructure which is built off a detailed threat model with thousands of security controls. Source: about 4 years ago
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / about 5 hours ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / about 11 hours ago
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 10 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 12 days ago
Fallback chains โ og:title โ twitter:title โ- SSRF protection โ if you fetch user-supplied URLs, you MUST block
localhost, RFC-1918 ranges, and internal hostnames, or your preview endpoint is a proxy into your own infrastructure- Caching โ you do not want to re-fetch a URL on every render
- Rate limiting โ a public...
- Source: dev.to / 14 days ago
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