Disaster Recovery and Fallbacks in AnySwap Bridges

Cross-chain bridges have a simple promise on the surface, yet the engineering beneath is anything but simple. Users deposit a token on chain A and expect to receive a corresponding asset on chain B within minutes. Under normal conditions, that flow works well. The challenge lies in what happens under stress: validator outages, chain halts, reorgs, congestion, RPC disconnects, volatile gas markets, or an exploit attempt. Disaster recovery is the quiet backbone of a bridge’s reliability, and the most respected teams treat it like a core product, not an afterthought.

This piece focuses on disaster recovery and fallback design patterns in AnySwap-style architectures. AnySwap began as a cross-chain liquidity network and has influenced many operational practices across bridge teams, from relayer orchestration to liquidity management and emergency procedures. Names and codebases evolve over time, but the lessons hold: build for failure, practice failover, and make user recovery predictable.

Failure domains in bridge operations

Every bridge lives across multiple failure domains at once. At a high level, you have the on-chain world, the off-chain services that glue chains together, and the people and processes who respond when something breaks. Each domain can fail independently, and their interactions can create surprising cascades.

On-chain risks cluster around consensus instability and permissioned keys. A validator set might stall, a chain might hard fork without finality, or a token contract could be paused. The bridge’s own contracts can introduce risk if they rely on parameters that are too optimistic for hostile conditions. For example, an unsafe assumption about block times can shrink safety margins during network congestion.

Off-chain infrastructure is far from glamorous but often dictates uptime. Relayers, watchers, indexers, and oracles rely on RPC providers, databases, message queues, and signing modules. A single overloaded PostgreSQL node, or a poorly tuned retry policy, can back up transfers across multiple chains. Gas price estimation, if naive, can result in stuck transactions that need manual repricing across dozens of networks.

Human processes are the final layer. Emergency key ceremonies, incident channels, and runbooks decide whether an outage lasts ten minutes or ten hours. Teams that drill their disaster plans tend to restore normal operations faster, with fewer side effects like mispriced liquidity or partial fills that create reconciliation headaches.

The anatomy of an AnySwap-style bridge

An AnySwap-style bridge typically implements two main flows: a lock-and-mint path and a burn-and-release path. Deposit on the source chain leads to either minting a representation on the destination chain or releasing pre-deposited liquidity. The bridge coordinates this with relayers that observe events, construct proofs or attestations, then submit those to destination contracts. Liquidity pools on both sides absorb volatility and mismatches in flow.

The best practice is to isolate responsibility. One set of services observes and attests, another handles transaction building and gas management, and a third reconciles state and flags anomalies. This separation makes it easier to throttle or halt specific components without freezing everything. For example, you might suspend minting on a destination chain while still allowing refunds on the source chain, or you might keep relayers observing events but pause submission until a contested fork settles.

What disaster recovery means in practice

Disaster recovery is not just about resuming service. It is about resuming correct service, with a truthful, auditable history. In cross-chain systems, correctness includes invariant preservation: total supply of wrapped assets must match locked collateral, no double mints, and no mismatched burns. When something goes wrong, the first step is often to protect those invariants, even if it means pausing user flows temporarily.

Teams need three muscles: detect, decide, and act.

Detect relies on instrumentation and watchers that alarm on anomalies. Decide requires a clear policy hierarchy for when to pause, partially degrade, or reroute. Act depends on the ability to execute playbooks safely under pressure, including key usage, contract pausing, and communication with users.

Detection: the signals that matter

Most outages announce themselves through lag, skew, or volatility. A bridge should measure:

• Finality latency per chain, including variance bands rather than averages.
• Relayer queue depth and age, ideally with percentiles, not just means.
• Gas price miss rates, such as the percentage of transactions that fail to land within N blocks.
• Liquidity imbalances across pools beyond normal directional flow.
• Orphaned events and inconsistent headers across indexers tied to the same chain.

Time-based budgets help. If a destination confirmation is expected within 7 minutes under normal load, alarms should fire at 2x or 3x the usual threshold so the team can intervene before users notice. False positives are inevitable, so tune alerts with backoff and deduplication.

Pausing the right thing, not everything

When conditions degrade, indiscriminate pausing causes more harm than good. You want circuit breakers that are narrow and layered. For instance, you might:

• Pause mints on chain X due to reorg risk while allowing burns and refunds on chain Y.
• Keep relayers syncing headers but block message submission to contracts until a safe checkpoint.
• Limit new deposits on a stressed route while settling in-flight transfers to avoid stranded funds.

The granularity matters. If the system allows chain-pair level toggles, the operations team can protect one route without affecting others. Pausing only on the destination side often gives users the ability to unwind from the source if they prefer, reducing support load and preserving trust.

Fallback designs for attestations and relayers

Relayers fail, and that is fine as long as they fail independently. AnySwap-style setups often feature multiple relayers with different RPC providers, geographic distribution, and diverse gas strategies. Diversity is not decoration, it is a recovery plan.

A battle-tested approach uses priority tiers. Primary relayers submit under ordinary conditions, with aggressive fee management tuned for cost efficiency. Secondary relayers sit mostly idle, sampling chain state but only waking fully when primary relayers miss target SLAs or when watchers detect unconfirmed transactions aging beyond set thresholds. A tertiary path can rely on a simplified stateless client, reserved only for deep emergencies where the stateful pipeline is compromised.

Consensus for cross-chain messages needs redundancy too. If the design uses threshold signatures or multi-party computation, then key shards should be distributed across clouds and regions, with distinct HSM vendors or enclaves where feasible. If the bridge relies on validator attestations, validator sets should rotate and avoid concentration with overlapping infrastructure providers. An otherwise healthy signature scheme becomes brittle if half the signers share the same DNS provider and that provider goes down.

Handling chain halts and deep reorgs

Chain halts come in two flavors: explicit pauses by chain governance and accidental stalls. Governance pauses are easier to detect and explain. Accidental stalls demand careful handling because they often precede contentious restarts or reorgs.

When a chain halts, the safest path is to freeze state-dependent actions that rely on that chain’s finality assumptions. Keep reading headers if possible, but do not act on them until the halt clears. For transfers initiated just before the halt, maintain an internal queue with a visible status for users. Do not burn or mint against half-settled facts.

Deep reorgs are worse. They can invalidate observed events and lead to double counting if relayers or watchers do not reconcile. Good practice is to treat reorg depth budgets as strict. If the chain historically reorgs up to 2 blocks in rare cases, set operational buffers higher, say 6 to 12 blocks depending on volume and economic stakes. During abnormal conditions, temporarily raise the buffer to prevent premature mints. The cost is longer settlement, but it is cheaper than a supply mismatch that requires manual clawbacks.

Liquidity as a recovery tool, not a risk amplifier

Liquidity lets a bridge complete transfers quickly, but it can also amplify loss if mismanaged during incidents. Two principles help:

First, model liquidity separately from finality. If you rely on liquidity to fulfill transfers before the source is irrevocably settled, ensure you have slippage and stop conditions that reflect chain health. When alarms trigger, squash the bridge’s appetite for new risk by throttling transfers that would consume liquidity faster than confirmations arrive.

Second, use invariant checks and reconciliation sweeps. Periodic reconciliation should compare minted balances and released collateral across all routes. During recovery, run these sweeps more frequently, even if it costs performance. Better to slow down than to compound an error over hundreds of transfers.

Anecdotally, the most painful post-incident week I have seen involved a bridge that kept a queue open while a destination chain suffered sporadic reorgs. The team minting on the destination thought the source had settled because their indexer was lagging. A hundred transfers later, they discovered a multi-block rollback wiped out the source events. The cleanup took days, required custom proofs, and strained the support team. A simple throttle once the first reorg hit would have contained the blast radius.

Key management during emergencies

Emergencies are the worst time to improvise with keys. If the system relies on signers for pausing contracts, upgrading parameters, or migrating funds, those signers must be reachable and distributed. No single executive with a laptop in one timezone should control a pause switch.

Use tiered access. Routine operations should sit behind lower-risk keys with limited permissions, such as adjusting gas parameters or toggling relayers. High-impact actions like pausing a bridge contract or altering withdrawal logic should require multi-party approval. Time-locks are valuable during normal operations but can be problematic in a true incident, so some teams include an emergency brake with a shorter or zero delay that is guarded by a distinct quorum and strict audit trails.

Log everything. Incident reviews depend on knowing who did what and when. Hardware wallets with attestation, strong identity management for operators, and immutable log sinks help keep the data clean. During recovery, a signed change log also reassures partners and users that actions were controlled.

RPC and indexer diversity

RPC instability accounts for a surprising share of bridge hiccups. A robust setup uses multiple providers with health checks, automatic failover, and reconnection strategies that avoid stampeding. Caching recent headers locally reduces pressure on external endpoints. If your relayers rely on block subscription streams, add a polling fallback that can pick up the slack when websockets flake.

Indexers deserve the same care. Consider running at least two independent pipelines, ideally with different client software and database backends. Cross-compare their views of chain state. If they diverge, treat it as a yellow flag and slow down submissions until they converge or the discrepancy is understood.

Gas management under stress

Gas spikes are a fact of life. The trick is to avoid turning a spike into a stall. Bridges should separate fee estimation from transaction urgency. For example, use a banded strategy: normal traffic uses a mid-percentile target fee, but urgent retries for stuck transactions escalate quickly within defined caps. Watch for nonce contention, especially if multiple workers share a hot account. A queue with nonce management and backpressure can prevent a wall of replacements that burn fees without progress.

Some operations teams keep a small fleet of funded “hot” accounts to drain queues during severe congestion. Rotate them carefully, and reconcile their nonces daily to avoid long-term drift. On chains with EIP-1559-style fees, track base fee trends and adjust tips separately, rather than relying on static multipliers that fail in volatile moments.

Communication that calms, not inflames

The best incident response includes steady, factual communication. Users do not need internal stack traces, but they deserve clarity about status, scope, and expected timelines. Publish incident posts early, even if brief. Acknowledge uncertainty and provide the next update time. If refunds are an option, say so and explain the path. Support queues shrink dramatically when the public channel answers the same questions upfront.

After resolution, write a root cause analysis in plain language. Include the change that triggered the event, the specific detection signals, why the failover did or did not work, and what will change. In my experience, partners judge teams more on the quality of their postmortems than on whether they had an outage. Outages happen. Hiding them corrodes trust.

Drills and tabletop exercises

Bridges serve global users at all hours, so the incident drill must be more than a checklist living in a wiki. Do dry runs. Simulate failed RPCs, stalled relayers, or a chain that stops finalizing. Time how long it takes to detect and pause the right routes. Make sure on-call teams in different time zones can reach the keys they need. Rotate roles so muscle memory spreads through the team, not just among a few senior operators.

Treat drills as a space to find awkward truths. Perhaps the emergency pause requires a signer who never travels without a security token that fails at airport checkpoints. Perhaps the database backup looks fine but restoration takes two hours longer than the SLA assumes. Better to discover those frictions during a drill than during a live incident.

Designing for partial degradations

Not all incidents demand a full stop. A hallmark of mature bridges is the ability to offer a degraded but safe service while recovering. For example, a bridge might switch from a fast path using liquidity to a slower path that waits for multiple confirmations. Fees could be adjusted to reflect the slower settlement. A UI banner can set expectations, reducing user frustration.

In some cases, it is appropriate to invert the flow. If destination chain conditions are poor, offer users a convenient refund mechanism on the source chain. Do this with clear rules: specify the timeout, any fees, and the precise state at which refunds become available. Avoid ad hoc promises that require manual handling later.

Recovery of stuck or ambiguous transfers

Inevitably, a subset of transfers will sit in limbo after an incident. These require careful classification. Typically they fall into categories like: source confirmed but not minted, minted but not yet claimable, or minted under a state that was later reverted. Each class demands a distinct remedy, documented in advance.

A reliable pattern uses a dedicated recovery contract or admin function that allows operators, under strict signatures, to finalize a transfer or reverse it after evidence-based verification. Evidence might be a Merkle proof from the source chain, an on-chain attestation, or a threshold-signed statement by the validator set. The bar should be high, and the process should leave an on-chain trail so auditors can verify that each recovery action corresponded to a real event.

Governance coordination and external dependencies

Cross-chain bridges rarely operate in a vacuum. They connect to chain foundations, token issuers, custodians, and liquidity partners. During incidents, coordination with these groups can accelerate safe recovery. For instance, if a token issuer can pause a token on a destination chain, a quick conversation can prevent malicious drains while the bridge sorts out finality concerns. Conversely, a chain’s emergency upgrade might require the bridge to adjust parameters or to pause for a predefined window.

Build those relationships before you need them. Maintain current contacts, escalation paths, and a directory of AnySwap key stakeholders. Keep a record of the bridge’s deployment addresses and permissions across chains so counterparties can validate actions without guesswork.

Post-incident accounting and reconciliation

After an incident, the story is not over until accounting reconciles every cent. This is where disciplined data pays off. Compare transfer logs, on-chain events, relayer submissions, and liquidity pool deltas. Create a ledger entry for each discrepancy, then resolve them one by one. Some will require user-facing fixes, such as crediting a missed mint or collecting a duplicated payout. Others will involve internal offsetting entries, like rebalancing pools or recording operational losses.

Do not rush this step. Teams that re-open a route before finishing reconciliation often face a second, preventable incident when hidden imbalances surface later. If you owe users funds, publish the plan and timeline, along with an email or wallet message for affected addresses.

Security layers that reduce blast radius

Security mitigations should aim to limit what Anyswap a single bug or key compromise can do. Rate limit critical functions, even on admin paths, and cap per-transaction amounts on routes with elevated risk. Compartmentalize deployers and operators so a compromise in one environment cannot immediately alter production contracts. If your architecture depends on off-chain services for safety checks, make sure they fail closed when they cannot reach required data.

Bug bounty programs help, but only if reports translate into changes. Where possible, add on-chain guards that reflect proven failure cases. For example, if an earlier incident exploited a timing window between attestations and mints, move critical checks on-chain, or enforce a minimal settlement delay that can be raised during alerts.

Lessons that endure

Bridges live in a messy environment, and no design eliminates all risk. The strongest AnySwap-style operations share a few habits that consistently improve outcomes:

• They plan for local failures without turning them into global outages. Chain-level and route-level controls give operators the precision they need.
• They prioritize invariant safety over throughput. When doubt rises, they slow or stop the path that can inflate supply or drain collateral.
• They maintain diversity in relayers, RPCs, indexers, and keys. Diversity prevents correlated failures from taking the bridge offline.
• They communicate clearly, with public updates that neither minimize nor dramatize. Users can forgive downtime more easily than opacity.
• They practice. Drills, postmortems, and continuous tuning make disaster recovery a routine craft rather than a heroic scramble.

A practical checklist operators can keep handy

• Define and test route-level pause switches, not just a global kill switch.
• Maintain secondary relayers with distinct infrastructure and gas policies, and verify automated failover monthly.
• Track finality and reorg metrics per chain, with dynamic safety margins during volatility.
• Document refund and recovery procedures with on-chain evidence requirements, and rehearse them.
• Keep an updated contact map of chain teams, RPC providers, and token issuers for fast coordination.

Closing thoughts

Resilience is not a single feature, it is the sum of many careful decisions. AnySwap-style bridges, when operated with discipline, can weather halts, reorgs, and infrastructure failures without losing funds or trust. The work is unglamorous: redundant relayers that idle for months, alert thresholds that change with market cycles, incident write-ups that dissect uncomfortable truths. Yet this steady investment is what earns the right to move value across chains at scale.

The measure of a bridge is not how it behaves when mempools are quiet and block times are steady. The measure is how it behaves on a Sunday night when a chain restarts after a contentious fork, gas prices triple, and a validator set rotates mid-epoch. Teams that build for that night, and practice for it, are the ones that keep user funds safe and reputations intact.