Fixed spatial Entropy scoring. Added sequence scoring.

adjacency/adjcmartix.go

@@ -16,36 +16,35 @@ type AdjacencyGraph struct {
 
 var AdjacencyGph = make(map[string]AdjacencyGraph);
 func init() {
-	//todo get currentloc so that i don't have to know the whole path
 	log.SetFlags(log.Lshortfile)
-	AdjacencyGph["qwerty"] = buildQwerty()
-	AdjacencyGph["dvorak"] = buildDvorak()
-	AdjacencyGph["keypad"] = buildKeypad()
-	AdjacencyGph["macKeypad"] = buildMacKeypad()
+	AdjacencyGph["qwerty"] = BuildQwerty()
+	AdjacencyGph["dvorak"] = BuildDvorak()
+	AdjacencyGph["keypad"] = BuildKeypad()
+	AdjacencyGph["macKeypad"] = BuildMacKeypad()
 }
 
-func buildQwerty() AdjacencyGraph {
+func BuildQwerty() AdjacencyGraph {
 	data, err := zxcvbn_data.Asset("data/Qwerty.json")
 	if err != nil {
 		panic("Can't find asset")
 	}
 	return GetAdjancencyGraphFromFile(data, "qwerty")
 }
-func buildDvorak() AdjacencyGraph {
+func BuildDvorak() AdjacencyGraph {
 	data, err := zxcvbn_data.Asset("data/Dvorak.json")
 	if err != nil {
 		panic("Can't find asset")
 	}
 	return GetAdjancencyGraphFromFile(data, "dvorak")
 }
-func buildKeypad() AdjacencyGraph {
+func BuildKeypad() AdjacencyGraph {
 	data, err := zxcvbn_data.Asset("data/Keypad.json")
 	if err != nil {
 		panic("Can't find asset")
 	}
 	return GetAdjancencyGraphFromFile(data, "keypad")
 }
-func buildMacKeypad() AdjacencyGraph {
+func BuildMacKeypad() AdjacencyGraph {
 	data, err := zxcvbn_data.Asset("data/MacKeypad.json")
 	if err != nil {
 		panic("Can't find asset")

match/match.go

@@ -23,6 +23,8 @@ type Match struct {
 	MatchedWord    string
 	Rank           float64
 	DictionaryName string
+	DictionaryLength int
+	Ascending bool
 	Turns          int
 	ShiftedCount   int
 	Entropy        float64

matching/matching.go

@@ -19,6 +19,8 @@ var (
 	KEYPAD_STARTING_POSITIONS int
 	KEYPAD_AVG_DEGREE float64
 	L33T_TABLE adjacency.AdjacencyGraph
+
+	SEQUENCES map[string]string
 )
 
 const (
@@ -29,7 +31,7 @@ const (
 
 
 func init() {
-
+loadFrequencyList()
 }
 
 func Omnimatch(password string, userInputs []string) (matches []match.Match) {
@@ -70,9 +72,16 @@ func loadFrequencyList() {
 	//	l33tFilePath, _ := filepath.Abs("adjacency/L33t.json")
 	//	L33T_TABLE = adjacency.GetAdjancencyGraphFromFile(l33tFilePath, "l33t")
 
+	SEQUENCES = make(map[string]string)
+	SEQUENCES["lower"] = "abcdefghijklmnopqrstuvwxyz"
+	SEQUENCES["upper"] = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+	SEQUENCES["digits"] = "0123456789"
+
 	MATCHERS = append(MATCHERS, DICTIONARY_MATCHERS...)
 	MATCHERS = append(MATCHERS, spatialMatch)
 	MATCHERS = append(MATCHERS, repeatMatch)
+	MATCHERS = append(MATCHERS, SequenceMatch)
+
 
 }
 
@@ -379,3 +388,61 @@ func repeatMatch(password string) []match.Match {
 	}
 	return matches
 }
+
+func SequenceMatch(password string) []match.Match {
+	var matches []match.Match
+	for i := 0; i < len(password); {
+		j := i + 1
+		var seq string
+		var seqName string
+		seqDirection := 0
+		for seqCandidateName, seqCandidate := range SEQUENCES {
+			iN := strings.Index(seqCandidate, string(password[i]))
+			var jN int
+			if j < len(password) {
+				jN = strings.Index(seqCandidate, string(password[j]))
+			} else {
+				jN = -1
+			}
+
+			if iN > -1 && jN > -1 {
+				direction := jN - iN
+				if direction == 1 || direction == -1 {
+					seq = seqCandidate
+					seqName = seqCandidateName
+					seqDirection = direction
+					break
+				}
+			}
+
+		}
+
+		if seq != "" {
+			for ;; {
+				var prevN, curN int
+				if j < len(password) {
+					prevChar, curChar := password[j - 1], password[j]
+					prevN, curN = strings.Index(seq, string(prevChar)), strings.Index(seq, string(curChar))
+				}
+
+				if j == len(password) || curN - prevN != seqDirection {
+					if j - i > 2 {
+						matches = append(matches, match.Match{Pattern:"sequence",
+							I:i,
+							J:j-1,
+							Token:password[i:j],
+							DictionaryName:seqName,
+							DictionaryLength: len(seq),
+							Ascending:(seqDirection == 1)})
+					}
+					break
+				} else {
+					j += 1
+				}
+
+			}
+		}
+		i = j
+	}
+	return matches
+}

scoring/scoring.go

@@ -8,6 +8,7 @@ import (
 	"regexp"
 	"github.com/nbutton23/zxcvbn-go/utils/math"
 	"github.com/nbutton23/zxcvbn-go/matching"
+	"github.com/nbutton23/zxcvbn-go/adjacency"
 )
 
 
@@ -29,7 +30,7 @@ const (
 type MinEntropyMatch struct {
 	Password         string
 	Entropy          float64
-	MatchSequence    []match.Match //TODO ?
+	MatchSequence    []match.Match
 	CrackTime        float64
 	CrackTimeDisplay string
 	Score            int
@@ -37,7 +38,7 @@ type MinEntropyMatch struct {
 }
 
 /*
-Returns minimum entropy TODO
+Returns minimum entropy
 
     Takes a list of overlapping matches, returns the non-overlapping sublist with
     minimum entropy. O(nm) dp alg for length-n password with m candidate matches.
@@ -164,6 +165,8 @@ func calcEntropy(match match.Match) float64 {
 		entropy = spatialEntropy(match)
 	} else if match.Pattern == "repeat" {
 		entropy = repeatEntropy(match)
+	} else if match.Pattern == "sequence" {
+		entropy = sequenceEntropy(match)
 	}
 
 	match.Entropy = entropy
@@ -181,8 +184,8 @@ func dictionaryEntropy(match match.Match) float64 {
 func spatialEntropy(match match.Match) float64 {
 	var s, d float64
 	if match.DictionaryName == "qwerty" || match.DictionaryName == "dvorak" {
-		s = float64(matching.KEYBOARD_STARTING_POSITIONS)
-		d = matching.KEYBOARD_AVG_DEGREE
+		s = float64(len(adjacency.BuildQwerty().Graph))
+		d = adjacency.BuildKeypad().CalculateAvgDegree()
 	} else {
 		s = float64(matching.KEYPAD_STARTING_POSITIONS)
 		d = matching.KEYPAD_AVG_DEGREE
@@ -190,12 +193,12 @@ func spatialEntropy(match match.Match) float64 {
 
 	possibilities := float64(0)
 
-	lenght := float64(len(match.Token))
+	length := float64(len(match.Token))
 	t := match.Turns
 
 	//TODO: Should this be <= or just < ?
-	//Estimate the number of possible patterns w/ lenght L or less with t turns or less
-	for i := float64(2); i <= lenght + 1; i++ {
+	//Estimate the number of possible patterns w/ length L or less with t turns or less
+	for i := float64(2); i <= length + 1; i++ {
 		possibleTurns := math.Min(float64(t), i - 1)
 		for j := float64(1); j <= possibleTurns + 1; j++ {
 			x := zxcvbn_math.NChoseK(i - 1, j - 1) * s * math.Pow(d, j)
@@ -204,13 +207,12 @@ func spatialEntropy(match match.Match) float64 {
 	}
 
 	entropy := math.Log2(possibilities)
-
 	//add extra entropu for shifted keys. ( % instead of 5 A instead of a)
 	//Math is similar to extra entropy for uppercase letters in dictionary matches.
 
 	if S := float64(match.ShiftedCount); S > float64(0) {
 		possibilities = float64(0)
-		U := lenght - S
+		U := length - S
 
 		for i := float64(0); i < math.Min(S, U) + 1; i++ {
 			possibilities += zxcvbn_math.NChoseK(S + U, i)
@@ -221,6 +223,23 @@ func spatialEntropy(match match.Match) float64 {
 
 	return entropy
 }
+func sequenceEntropy(match match.Match) float64 {
+	firstChar := match.Token[0]
+	baseEntropy := float64(0)
+	if string(firstChar) == "a" || string(firstChar) == "1" {
+		baseEntropy = float64(0)
+	} else {
+		baseEntropy = math.Log2(float64(match.DictionaryLength))
+		if unicode.IsUpper(rune(firstChar)) {
+			baseEntropy ++
+		}
+	}
+
+	if !match.Ascending {
+		baseEntropy++
+	}
+	return baseEntropy + math.Log2(float64(len(match.Token)))
+}
 func extraUpperCaseEntropy(match match.Match) float64 {
 	word := match.Token