Your AI agents are live.You have no idea
what they're doing.

Manage your entire AI agent fleet from one platform. DapplePot monitors every action in real time, lets you control rogue sessions instantly, and protects your stack with automated OWASP coverage — so you can intervene before damage is done.

Sessions
All environments · Last 24h
TOTAL SESSIONS
1,247
↑ 12% · prev 24h
STATUS
1,189done58flagged
95.4% completion rate
TOKENS
4.2M
2.8M in · 1.4M out
AVG LATENCY
312ms
p50 248 · p99 1.2s
SESSIONS · 6 activefilter: all
SESSION
AGENT
USER
STATUS
STARTED
DUR
7f2a3b1f
sales-copilot
u_4821
terminated
2m ago
12s
3c1e9a4b
sales-copilot
u_3912
completed
5m ago
8.2s
9k1xa2b1
support-bot
u_7723
active
6m ago
4a2c8b3d
support-bot
u_5520
completed
11m ago
24s
7m3nc4e5
data-analyst
u_8841
completed
14m ago
6.8s
2b4p1f6g
data-analyst
u_2218
completed
21m ago
18s
EVENT TIMELINE · 7f2a3b1f7 events · 1 alert
+0mssession_start
+340msllm_call · gpt-4o
+1.2stool_call · query_db
+3.4stool_result · 142 rows
+5.1s prompt_injection · OW-LLM01
+5.2ssession_terminated
+5.2s[exit: security_terminated]
duration: 5.2s · 3 tool calls · 1 alert
AGENTS
12
3 active · 9 idle
TOOLS · MCP
27+3
5 llm models linked
OWASP LLM RISK
72
HIGH · LLM Top 10
OWASP ASI RISK
65
HIGH · Agentic AI
AGENT SCOPEsales-copilot
privilegeread_onlyedit
tool_scope3 tools · 1 mcpedit
max_tools15 / sessionedit
token_budget25,000edit
llm_modelsgpt-4o · claudeedit
CHAIN ALERTactive
prompt_injectiontool_misusepriv_abuse
Subchecks triggered · 1h
OW-LLM01:sub_03×4
OW-ASI02:sub_07×2
OW-ASI03:sub_01×1
ONLINE DETECTION CHECKStoggle = online (inline) · 18 active
OW-LLM01Prompt Injectioncritical
OW-LLM02Data Disclosurecritical
OW-ASI02Tool Misusehigh
OW-ASI06Memory Poisoningmedium
TOP SIGNAL · CROSS-SESSION
OW-LLM01
Prompt Injection · ×23
TOP VULNERABLE AGENT
sales-copilot
risk score 72 · HIGH
FINDINGS · 24h
47
12 critical · 22 high
ACTIVE THREATS
3
↑ 1 since last hour
SESSION FINDINGS7f2a3b1f · 4 found
LLM Risk
72
ASI Risk
65
terminatedPrompt Injection
OW-LLM01:sub_03
+5.1s
sanitizedTool Misuse
OW-ASI02:sub_07
+3.4s
alertPII in Output
OW-LLM02:sub_02
+2.8s
alertHallucination Risk
OW-LLM09:sub_01
+1.5s
AGENT HEALTHfleet · 24h
AGENTRISKTRUSTTRENDDRIFT
sales-copilot7258high
support-bot4176stable
data-analyst5864medium
DETECTION ALERTSlast 1h
Prompt injection blockedsales-copilot
2m
Anomalous tool sequencesupport-bot
8m
Threshold breach near limitdata-analyst
23m
Routed to Slack Teams
01 · MONITOR
see every session
02 · CONTROL
tune every check
03 · PROTECT
block every threat
The blind spot

AI agents inherit
your blast radius.

Enterprises aren't deploying one agent. They're deploying fleets — and every fleet is a new risk surface.

  • Agents reading email, writing code, querying databases, and calling external APIs on behalf of real users
  • A single compromised session can move laterally across systems before anyone notices
  • The attack surface is no longer a perimeter — it's every autonomous decision your agent makes
?
Was the agent manipulated mid-session to act outside its intended scope?
?
Did it expose sensitive data or make a decision it shouldn't have?
?
Can you prove to your security team that your agent behaved safely?
?
If something went wrong, can you replay exactly what happened?
?
Do you know which agents in your fleet are drifting from expected behavior?
Runtime
< 100ms

While it happens

Threats caught and killed before they reach your users or external systems.

  • Inline threat detection
  • Live session kill switch
  • Tool call interception
  • Real-time alerts
● Active
Post-session
~30 seconds

After it runs

A complete, tamper-evident record of everything your agent did — automatically.

  • Full session replay
  • Immutable audit trail
  • OWASP finding map
  • Evidence for post-mortems
○ Analyzed
Cross-session
Continuous

Agent health

Behavioral trends, drift detection, and fleet-level risk scoring across all your agents.

  • Behavioral drift detection
  • Fleet health overview
  • Threat frequency trends
  • Session risk scoring
◈ Aggregated
Full lifecycle coverage

Not just runtime.
Every phase.
Every agent.

Most tools stop at “runtime.” DapplePot covers the full arc — from the first LLM call to cross-session health of your entire fleet.

See it in action

With 4 lines —
Complete runtime visibility.

Drop the SDK into your agent code and DapplePot starts monitoring immediately — every LLM call, tool use, and decision captured across the entire session.

Read the docs ↗
import anthropic
from dapplepot_sdk import DapplePot

# Initialize once — your credentials
dp = DapplePot(
    sdk_key    = "dp_sk_•••",
    tenant_id  = "acme-corp",
    agent_id   = "sales-copilot",
    ingest_url = "https://ingest.dapplepot.com",
)
dp.instrument_anthropic()

# Wrap each conversation in dp.session()
with dp.session(user_context_id="user_123"):
    response = anthropic.Anthropic().messages.create(
        model="claude-opus-4-7",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello!"}],
    )

# Runtime detection fires inline.
# Post-session audit runs automatically.
# Cross-session health tracked continuously.
Monitor

Session Replay

Every action, every call recorded in sequence. Replay any session frame by frame.

All agents
ALL AGENTS · RECENT SESSIONS
sales-copilot✓ Clean2m ago
support-bot⚠ Threat5m ago
data-analyst✓ Clean9m ago
Control

Live Control

Kill sessions instantly. Push policy updates to running agents without a redeploy. Set what is expected for each agent — any deviation raises a flag automatically.

Runtime
SESSION CONTROLS
prod-7f2a  ·  ACTIVE
pi01a identified
Protect

Threat Detection

Catch threats in runtime, post-session and cross-session to maintain a long-sighted lighthouse view of your entire agent fleet.

All phases
AGENT SCOPE · sales-copilot
privilegeread_only
tool_calls≤ 15 / session
external_apiblocked
data_exportnot allowed
What DapplePot gives you

Monitor.
Control.
Protect.

Full visibility, live intervention, and inline detection — without changing how your agents run or slowing them down.

Built for every stakeholder

One platform.
Three teams aligned.

DapplePot gives each stakeholder exactly what they need — from the same source of truth.

AI / ML Team

Ship faster.
Debug in minutes.

You built the agent. Now see what it actually does in production — not what you think it does in a notebook.

  • Replay any session to pinpoint exactly where it went wrong
  • Real inputs & outputs — not sanitized logs
  • Catch anomalies before users escalate
  • Understand tool usage patterns and optimize performance
We went from 'something broke' to root cause in under five minutes.
Security Team

Detect threats.
Prove coverage.

AI agents are your largest unmonitored attack surface. DapplePot brings them into your security perimeter.

  • Real-time detection for prompt injection, data leakage & privilege abuse
  • Full OWASP LLM Top 10 + Agentic AI Top 10 coverage
  • Instant kill switch for rogue sessions
  • Threat alerts routed to your existing channels
For the first time we could answer: is our agent behaving safely in production?
Audit / Compliance

An immutable record
of every decision.

When auditors ask what your agent did, "it seemed fine" won't cut it. DapplePot gives you the tamper-evident trail.

  • Timestamped record of every agent action — nothing omitted
  • Findings mapped to OWASP LLM + Agentic AI controls
  • Session-level evidence for incidents & post-mortems
  • Prove your AI governance controls are working
We used to say trust us. Now we can show them the receipts.
12+
events captured
complete flow
147+
security sub-checks
LLM Top 10 + Agentic AI
90 days
immutable event history
all sessions
Security coverage

Built around what actually threatens AI agents.

Full coverage across OWASP LLM Top 10 and OWASP Agentic AI Top 10 — the standards your security and compliance teams already recognize.

LLM Top 10
LLM01

Prompt Injection

Malicious inputs override agent instructions

LLM02

Data Disclosure

Sensitive data leaks through outputs

LLM03

Supply Chain

Not detectable at inference time

LLM04

Data Poisoning

Not detectable at inference time

LLM05

Insecure Output

Unvalidated output triggers harm downstream

LLM06

Excessive Agency

Agent acts beyond its sanctioned mandate

LLM07

System Prompt Leakage

Internal instructions exposed to users

LLM08

Vector Weakness

Some sub-checks excluded — pre-runtime only

LLM09

Misinformation

Hallucinated outputs delivered with confidence

LLM10

Unbounded Consumption

Runaway resource and cost abuse

Agentic AI Top 10
ASI01

Goal Hijacking

Agent objective redirected mid-session

ASI02

Tool Misuse

Tools exploited beyond intended scope

ASI03

Identity & Priv Abuse

Agent impersonates or escalates access

ASI04

Agentic Supply Chain

Compromised plugins or dependencies

ASI05

Unexpected Code Exec

Agent triggers unintended runtime actions

ASI06

Memory Poisoning

Persistent memory injected with malicious context

ASI07

Inter-Agent Comms

Multi-agent trust exploited to spread threats

ASI08

Cascading Failures

One failure triggers a chain reaction

ASI09

Trust Exploitation

Human over-reliance weaponized against users

ASI10

Rogue Agents

Agent operates entirely outside its boundaries