dsh-workflow-isolate
QuickJS/WASM-isolated WorkflowEngine for running model-written DeepSeek Harness orchestration with bounded resource controls.
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QuickJS/WASM-isolated WorkflowEngine for running model-written DeepSeek Harness orchestration with bounded resource controls.
DeepSeek Companion Enterprise — DeepSeek Harness 企业级伴侣插件:安全审计与 DLP、团队协作与知识管理、任务编排、多模型竞技场、执行轨迹分析、Prompt 工程工作台、API 成本治理。
Model-facing typed tools wrapping the frozen, reviewed underseal adapter for the DeepSeek Harness
Agent-decided approvals for DeepSeek Harness: a workspace-write base permission mode where an independent approval subagent judges every sandbox escalation (risky operations are rejected), with a configurable approval model and a per-session audit trail in the conversation window's 审批 tab.
A middle permission tier for DeepSeek Harness between workspace-write and danger-full-access: auto-approves harmless commands and operations targeting configured trusted areas, beyond the current workspace.
Find DSH plugins and security-scan them before install
Real-time attention alerts for DeepSeek Harness: a global banner plus flashing workspace entries when the agent is blocked (approval request / sandbox denial), with an audible chime and OS-level notifications for new blockers.
Cybersecurity and reverse-engineering skill router for coding agents (pi / DSH / Codex CLI / Claude Code). Explicitly invoke when reverse-engineering, security analysis, CTF, or pentesting workflow is required.
DeepSeek Harness plugin (temporary, pre-upstream-fix): automatically injects a CPython tempfile shim (PYTHONPATH -> sitecustomize) into every confined shell command on the Windows sandbox, so python/pytest tempfile use works with zero extra tools, zero model-context overhead, and zero escalation.
Security for DeepSeek Harness in two layers: source-backed pre-install vetting plus fail-closed runtime guardrails and HMAC-chained audit logs. Zero runtime dependencies.
Decision-driven AI company orchestration with HR governance, monetary budgets, model discovery, and deterministic audit for DeepSeek Harness
Content-addressed audit indexes across independent DeepSeek Harness evidence producers
Blaxel sandbox execution plugin for DeepSeek Harness (DSH)
Retrieved ≠ injected: CBDC-gated memory for DeepSeek Harness — decides how memory is USED (use/verify/ignore decisions, feedback learning, full audit); local SQLite + FTS5, bounded, no extra model call
Find and audit DeepSeek Harness (DSH) plugins inside the agent — live `dsh-plugin` topic search + source audit with trial-to-production install plans.
OMV Audit Desk: an evidence-first vulnerability audit workbench for DeepSeek Harness
DSH AI 代码安全审查插件:secure_scan/secure_diff/secure_fix_verify/secure_report/secure_export/secure_baseline/secure_deps/secure_policy_show/secure_policy_set 九工具,40+ 确定性规则、密钥熵检测、git diff/staged 审查、SARIF 导出、基线接受与 SBOM-lite,零运行时依赖。
Harness Plugin Store Optimized: a customized fork of dsh-plugin-hub — configurable plugin download directory, bundle-layer conflict detection, automatic pnpm lookup, and upstream bug fixes
自然语言查询 + 商业智能报表插件 for DeepSeek Harness:在 dsh-mysql 连接底座之上,提供 Text2SQL 自然语言查库、15+ 图表类型、Dashboard 仪表盘、指标/维度管理、多维分析、自助分析、报表导出、审计日志与数据权限。Natural-language data queries + enterprise BI reports for DeepSeek Harness: Text2SQL, 15+ chart types, dashboards, metric management, multi-dimensional analysis, self-service analysis, export, audit log and data permissions.
KISS's Law (Weiwen's Law) universal causal engine (white-box presentation). DeepSeek Harness (Cordis) plugin implementation.
DSH WebUI capability controls for skills, MCP servers, tools, prompt injections, approvals, and safety guards at session, project, and global levels.
Hard-stop consecutive identical DeepSeek Harness tool calls after a configurable streak.
Seatbelt (libsandbox) sandbox provider for the DeepSeek Harness sandbox seam on macOS: a cordis plugin that replaces @deepseek-ai/dsh-sandbox-local's seatbelt rung via a prebuilt seatbelt-run launcher — no dsh source changes, no PR required
Portable DSH WebUI skill security inspection with local rules and optional model review